CN114994693A - Laser ranging method and device - Google Patents

Abstract

The present application discloses a laser ranging method and device. The laser ranging method includes: providing a first storage space; within a first period of exposure time, storing and accumulating the trigger times of the TDC output in the first storage space to generate a coarse histogram corresponding to the coarse time accuracy; Select M peaks in the coarse histogram, and obtain coarse time bins corresponding to the M peaks; obtain complete time bins corresponding to the M peaks according to the coarse time bins corresponding to the M peaks; For the complete time bins corresponding to the peaks, M object distance measurements are determined. The laser ranging method does not need to save all the histogram data, and can significantly reduce the area of the ranging chip.

Description

Laser ranging method and device

technical field

The present application relates to the technical field of optical ranging, and in particular, to a laser ranging method and device.

Background technique

At present, a lidar measurement system based on dTOF (Directtimeofflight, direct time of flight) measurement usually includes a transmitter and a receiver, wherein the receiver usually adopts a SPAD (Single Photon Avalanche Diode, single photon avalanche diode) array to receive the returned Optical signal, and convert the time information into a quantized multi-bit digital signal through TDC (Time-to-Digital Converter), and then draw a distance-based statistical histogram after long-term exposure and TDC trigger accumulated value The distance information of the object is obtained according to the statistical histogram. However, this laser ranging method generally requires a complete statistical histogram for one pixel. The larger the size of the Static Random-Access Memory)) is, the larger the chip area of the ranging chip is.

SUMMARY OF THE INVENTION

In view of this, the embodiments of the present application provide a method and device for laser ranging, which are used to solve the problem of an excessively large chip area caused by the traditional method for implementing laser ranging using statistical histograms.

In a first aspect, an embodiment of the present application provides a laser ranging method, the method comprising:

There is a first storage space;

During the first exposure time, the trigger times of the TDC output are stored and accumulated in the first storage space to generate a coarse histogram corresponding to the coarse time precision;

Select M peaks in the coarse histogram, and obtain the coarse time bins corresponding to the M peaks;

Acquiring the complete time bins corresponding to the M peaks according to the coarse time bins corresponding to the M peaks specifically includes: storing the first data in the first storage space during the second exposure period, storing the TDC The real-time output time bin data is compared with the first data. The initial value of the first data is the coarse time bin corresponding to the first peak value. According to the comparison result, the first data is calculated by adding and subtracting The preset adjustment difference is updated, and the updated first data is the complete time box corresponding to the first peak value. During the exposure time of the M+1th segment, in the first storage The Mth data is stored in the space, and the time box data output by the TDC in real time is compared with the Mth data. The initial value of the Mth data is the coarse time box corresponding to the Mth peak. According to the comparison result, The Mth data is updated by adding and subtracting the adjustment difference, and the updated Mth data is the complete time box corresponding to the Mth peak;

M objects distance measurements are determined according to the complete time bins corresponding to the M peaks.

The above aspect and any possible implementation manner further provide an implementation manner in which the time box data output by the TDC in real time is compared with the first data, and the initial value of the first data is the first The coarse time bins corresponding to the peak values, according to the comparison result, the first data is updated by adding and subtracting a preset adjustment difference, including:

Compare the time box data output by the TDC in real time with the first data, and if the first data is smaller than the time box data output by the TDC in real time, then the first data plus the adjustment difference is obtained. The updated first data is stored in the first storage space;

If the first data is greater than the time box data output by the TDC in real time, the first data is subtracted from the adjustment difference to obtain the updated first data, which is stored in the first storage space ;

If the first data is equal to the time box data output by the TDC in real time, the first data is reserved and stored in the first storage space.

In the above aspect and any possible implementation manner, an implementation manner is further provided, wherein the range of the adjustment difference is set according to the coarse time precision of the coarse histogram, when the coarse time precision is lower , the value of the adjustment difference will be larger.

The above aspect and any possible implementation manner further provide an implementation manner. The selecting M peaks in the rough histogram includes: sorting all peaks in the rough histogram according to peak size , from large to small, M peaks are selected; or, by setting a peak threshold, M peaks larger than the peak threshold are selected.

The above-mentioned aspect and any possible implementation manner further provide an implementation manner, and the method further includes:

A second storage space is provided, and the storage capacity of the second storage space is larger than that of the first storage space;

During the second exposure time, the first data is stored in the first storage space, and the time box data output by the TDC in real time is compared with the first data. The initial value of the first data is the first Each of the coarse time bins corresponding to the peak values, according to the comparison result, the first data is updated by adding and subtracting the adjustment difference, and is stored in the second storage space at the same time. The storage capacity can store N historical values of the first data. During the exposure time of the M+1th segment, the Mth data is stored in the first storage space, and the time box data output by the TDC in real time and the M data are compared, the initial value of the M th data is the coarse time bin corresponding to the M th peak, and according to the comparison result, the M th data is updated by adding and subtracting the adjustment difference, and at the same time Stored in the second storage space, the storage capacity of the second storage space can store N historical values of the Mth data;

Calculate the average value of the historical value of the N described first data, and so on, according to the exposure time period, calculate to obtain the average value of the historical value of the Mth data within the Nth M+1 exposure time;

According to the average value of the historical values of the N pieces of the first data and the average value of the historical values of the Mth data from the exposure time period to the N M+1th exposure times, the M distances of the objects are determined Measurements.

According to the above aspect and any possible implementation manner, an implementation manner is further provided, wherein the first storage space is a first-in, first-out memory.

The above-mentioned aspect and any possible implementation manner further provide an implementation manner, and the method further includes:

Get the peak preset interval range;

According to the preset interval range of the peaks, re-determining the M peaks on the basis of the M peaks;

The corresponding complete time bins are acquired according to the re-determined M peaks.

In the above aspect and any possible implementation manner, an implementation manner is further provided, wherein the adjustment difference value includes a first adjustment difference value and a second adjustment difference value, and the value of the first adjustment difference value is greater than the The value of the second adjustment difference, the adjustment difference is changed according to the number of times of receiving the TDC, wherein when the number of comparisons reaches a preset threshold, the first adjustment difference is changed to the second adjustment difference .

In a second aspect, an embodiment of the present application provides a laser ranging device, and the device includes:

Laser transmitter for emitting laser light;

SPAD array for receiving optical signals;

TDC arrays for converting the time-of-flight of optical signals into digital signals;

The coarse histogram control circuit is used for storing and accumulating the trigger times of the TDC output in the first storage space during the first exposure time, so as to generate a coarse histogram corresponding to the coarse time precision; Select M peaks in the histogram, and obtain the coarse time bins corresponding to the M peaks;

a memory for storing the coarse time bins corresponding to the M peaks in the coarse histogram;

A complete time bin adjustment control circuit, configured to obtain the complete time bins corresponding to the M peaks according to the coarse time bins corresponding to the M peaks, specifically including: during the second exposure time period, in the first exposure time The storage space stores the first data, and compares the time bin data output by the TDC in real time with the first data. The initial value of the first data is the coarse time bin corresponding to the first peak value. According to the comparison result , the first data is updated by adding and subtracting a preset adjustment difference, and the updated first data is the complete time box corresponding to the first peak value, and is exposed in the M+1 segment During the time, the Mth data is stored in the first storage space, and the time box data output by the TDC in real time is compared with the Mth data, and the initial value of the Mth data is the Mth corresponding to the peak value. For the coarse time box, according to the comparison result, the Mth data is updated by adding and subtracting the adjustment difference, and the updated Mth data is the complete time box corresponding to the Mth peak;

A readout circuit, configured to determine M distance measurement values of objects according to the complete time bins corresponding to the M peaks.

Further, the apparatus further includes a second storage space and a computing unit, wherein the storage capacity of the second storage space is larger than that of the first storage space;

The complete time box adjustment control circuit is further configured to store the first data in the first storage space during the second exposure time period, and compare the time box data output by the TDC in real time with the first data , the initial value of the first data is the coarse time box corresponding to the first peak value, and according to the comparison result, the first data is updated by adding and subtracting the adjustment difference, and is stored in the In the second storage space, the storage capacity of the second storage space can store N historical values of the first data, and within the exposure time of the M+1th segment, the Mth data is stored in the first storage space, Compare the time box data output by TDC in real time with the Mth data, the initial value of the Mth data is the coarse time box corresponding to the Mth peak, and according to the comparison result, the Mth data passes through. Add and subtract the adjustment difference to complete the update, and save it in the second storage space at the same time, and the storage capacity of the second storage space can store N historical values of the Mth data;

The calculation unit is used to calculate the average value of the historical values of the N first data, and so on, according to the exposure time period, to obtain the history of the Mth data within the Nth M+1 exposure time. the average of the values;

The readout circuit is further configured to calculate the average value of the historical values of the Mth data according to the average value of the historical values of the N pieces of the first data and the average value of the historical values of the Mth data according to the exposure time period to the Nth M+1th exposure time value to determine M distance measurements of the object.

In the embodiment of the present application, a first storage space is provided. During the first period of exposure time, the trigger times of the TDC output are stored and accumulated in the first storage space to generate a coarse histogram corresponding to the coarse time accuracy. The method of histogram can reduce the storage requirement, and can roughly describe the data situation of the complete histogram; then select M peaks in the coarse histogram, and obtain the coarse time bins corresponding to the M peaks, which can further reduce the storage. Requirement, select the coarse time bins with peak characteristics from the coarse histogram to quickly determine the coarse time bins related to the object distance measurement value when performing distance detection on multi-target objects; then obtain the coarse time bins corresponding to the M peaks. The complete time bins corresponding to the M peaks, after positioning the coarse time bins, on the basis of the coarse time bins, the coarse time bins corresponding to the peak values are continuously updated and adjusted through each numerical comparison, so that the coarse time bins are at the initial value At the same time, it quickly converges to the vicinity of the actual object distance measurement value, and obtains a complete time box that can accurately reflect the object distance detection; finally, according to the complete time box corresponding to the M peaks, the M object distance measurement values are determined. Using the laser ranging method does not need to save all the histogram data, which can significantly reduce the area of the ranging chip.

Description of drawings

In order to illustrate the technical solutions of the embodiments of the present application more clearly, the following briefly introduces the accompanying drawings used in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can also be obtained from these drawings without any creative effort.

1 is a schematic structural diagram of realizing optical ranging in the prior art;

Fig. 2 is the schematic flow chart that adopts the optical ranging method to realize histogram statistics in the prior art;

FIG. 3 is a flowchart of a laser ranging method in an embodiment of the present application.

Detailed ways

In order to better understand the technical solutions of the present application, the embodiments of the present application are described in detail below with reference to the accompanying drawings.

It should be clear that the described embodiments are only a part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. As used in the embodiments of this application and the appended claims, the singular forms "a," "the," and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise.

It should be understood that the term "and/or" used in this document is only one of the same fields to describe the associated objects, indicating that three relationships can exist, for example, A and/or B, which can mean: A alone exists, and A exists at the same time and B, there are three cases of B alone. In addition, the character "/" in this document generally indicates that the related objects are an "or" relationship.

It should be understood that although the terms first, second, third, etc. may be used in the embodiments of the present application to describe the preset range and the like, these preset ranges should not be limited to these terms. These terms are only used to distinguish preset ranges from one another. For example, without departing from the scope of the embodiments of the present application, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

Depending on the context, the word "if" as used herein can be interpreted as "at" or "when" or "in response to determining" or "in response to detecting." Similarly, the phrases "if determined" or "if detected (the stated condition or event)" can be interpreted as "when determined" or "in response to determining" or "when detected (the stated condition or event)," depending on the context )" or "in response to detection (a stated condition or event)".

FIG. 1 is a schematic structural diagram of realizing optical ranging in the prior art. As shown in FIG. 1 , the lidar device 100 includes a laser emitting device 110 , a control module 120 , a SPAD module 140 , a TDC module 150 and a memory 160 . When realizing optical ranging, the laser emitting device 110 emits laser light, and the photons are irradiated on the target object 130 through the lens, and the target object 130 is continuously exposed. During exposure of the target object 130, photons are irradiated back through the lens to the lidar device 100 by reflection. The lidar device 100 receives the returned optical signal through the SPAD module 140, and converts the time information into a quantized multi-bit digital signal through the TDC module 150, and then draws a distance-based dynamic histogram based on the long-term exposure and TDC trigger accumulated value to obtain the distance information of the target object 130 . The control module 120 is configured to control the SPAD module 140, the TDC module 150 and the memory 160 to complete the storage of statistical histogram data.

It should be noted that, in addition to the target object 130 in the figure, the lidar device can also support distance detection for multiple target objects at the same time, and the detection quantity of the target objects is not limited here.

It can be understood that the SPAD module 140 includes many SPAD units, and each SPAD unit can realize the sensing detection of photons. The resolution is, for example, 320*240, or 640*480. When the resolution is higher, the required scale and storage capacity of the TDC module 150 and the memory 160 that complete the histogram statistics at the later stage are higher. Generally, one SPAD unit corresponds to a complete statistical histogram. In a statistical histogram, the abscissa represents time (it can also represent distance, and D=C*TOF/2, where D represents distance, TOF is digital information converted into time according to time information, and C represents the speed of light) , where the minimum scale on the abscissa represents a time bin (time bin), which corresponds to the minimum precision of the TDC; the ordinate represents the cumulative count value of each time bin within a period of time. It can be seen that for the storage requirements of the ranging chip, to achieve long-distance laser ranging, the depth of the memory is required to be large enough (it can store enough timebins); to achieve a high signal-to-noise ratio, the memory is required. The bits are wide enough (to store a larger accumulated count value). Assuming that there is a dTOF receiver with 80x60=4800 pixels (SPAD unit), the TDC data bit width is 10 bits, the minimum precision is 0.1ns (corresponding to a distance of 1.5cm), and each time bin is represented by an 8-bit count value (maximum count The value is 255), for the requirement of the farthest detection distance of 6m (corresponding to 400 timebins, 400*1.5cm=6m), the minimum memory size required for one frame of image is: 400*8*4800=15.36Mbit=1.92Mbyte, If the resolution becomes 320x240=76800 and the farthest detection distance is still 6m, the memory size required for one frame of image becomes: 400*8*76800=245.76Mbit=30.72Mbyte, it can be seen that with the resolution of the area array lidar As the rate becomes higher and higher, the scale of the TDC array and memory for post-processing will be larger, and the chip area of the ranging chip will also increase accordingly.

FIG. 2 is a schematic flow chart of implementing histogram statistics by using an optical ranging method in the prior art. As shown in FIG. 2 , for SPAD (unit) 1, it uses TDC (unit) 1 to determine the accumulative count position that the SPAD1 needs in Memory1 (storage unit 1) by means of addressing. Among them, Memory1 can specifically include 1024 timebins with a width of 10 bits. When the object is continuously exposed, Memory1 will count the optical signals received on SPAD1, and finally output the statistical data as the actual result, with timebin as the abscissa A statistical histogram is generated with the ordinate as the cumulative count value of each timebin over a period of exposure time. Similarly, Memoryn (the nth memory cell) may include 1024 10-bit wide timebins, during the exposure of the object, Memory1 will count the light signals received on SPADn (the nth SPAD cell) and put the SPADn The corresponding statistical histogram output.

It can be understood that, since the ranging method adopts the method of histogram statistics, in the case of long-distance laser ranging or high resolution, the scale of the memory 160 of the lidar device 100 will become very large, which is very difficult for the lidar. The storage requirement of the device 100 is high, which will result in an excessively large chip area of the ranging chip.

In view of the problem that the chip area is too large in the above-mentioned statistical histogram to realize the laser ranging method, the present application proposes a laser ranging method and a laser ranging device.

FIG. 3 is a flowchart of a laser ranging method in an embodiment of the present application. As shown in Figure 3, the laser ranging method includes the following steps:

S10: A first storage space is provided.

In one embodiment, a first storage space is configured for the lidar device, and the first storage space is much smaller than the storage capacity for storing the complete statistical histogram, and is mainly used for storing the distance detection value from the object in the statistical histogram. The relevant data (the coarse time bins corresponding to the M peaks) are used to calculate the object detection distance value more accurately by using the data related to the object distance detection value.

S20: During the first exposure time, store and accumulate the trigger times of the TDC output in the first storage space to generate a coarse histogram corresponding to the coarse time precision.

In one embodiment, the lidar device exposes the target object by emitting photons, and within the exposure time, the preset coarse time precision is used to store and accumulate the trigger times of the TDC output in the first storage space to generate a corresponding coarse histogram. picture. It is understandable that the minimum precision of the complete statistical histogram is one time bin unit. To generate a coarse histogram according to the coarse time precision, a combination of multiple minimum precision time bins can be used, and the combined new time bin can be used as the unit of time bin. New minimum precision unit; or, divide the maximum range of the TDC according to the preset time distribution, so that during the first exposure time, the lidar device stores and accumulates the number of triggers output by the TDC according to the divided time unit to generate corresponding The rough histogram of . It can be understood that since the time bin of the minimum precision is not used for drawing the histogram, the storage capacity requirement of the first storage space will be significantly reduced.

S30: Select M peaks in the coarse histogram, and obtain coarse time bins corresponding to the M peaks.

The value of the ordinate of the complete statistical histogram (that is, the number of triggers output by the TDC) is a curve, and the curve can include multiple peaks, which can be used as multi-target object distance measurement values during multi-target detection. In this embodiment of the present application, M peaks are selected in the coarse histogram, and coarse time bins corresponding to the M peaks are acquired. Understandably, since it is a coarse histogram, the selected M peaks do not represent the peaks in the complete statistical histogram, so the time bins corresponding to the M peaks may be called coarse time bins.

S40: Acquire complete time bins corresponding to the M peaks according to the coarse time bins corresponding to the M peaks.

Wherein, the step S40 specifically includes: within the second exposure time, storing the first data in the first storage space, comparing the time box data output by the TDC in real time with the first data, and the initial value of the first data is the first According to the comparison result, the first data is updated by adding and subtracting the preset adjustment difference, and the updated first data is the complete time box corresponding to the first peak, which is in the M+1 segment. During the exposure time, the Mth data is stored in the first storage space, and the time box data output by the TDC in real time is compared with the Mth data. The initial value of the Mth data is the coarse time box corresponding to the Mth peak. According to the comparison result, The Mth data is updated by adding and subtracting the adjustment difference, and the updated Mth data is the complete time box corresponding to the Mth peak.

Understandably, the first exposure time obtains the coarse time bins corresponding to the M peaks. These coarse time bins can roughly represent the object detection distance of multiple targets. In the embodiment of the present application, the coarse time bins corresponding to the M peaks will be numerically updated, so that the updated coarse time bins are closer to the time bins corresponding to the peaks in the complete statistical histogram. The bins approach the accurate time bins, and the time bins finally updated by numerical comparison can be called complete time bins.

In one embodiment, for multi-target object detection, since different peak values correspond to different object distance measurement values, it is necessary to update and adjust the coarse time bin corresponding to each peak value. The value of the coarse time box is compensated accordingly according to the value difference of the coarse time box corresponding to the peak value. Or subtract the adjustment difference. Among them, each exposure only performs numerical adjustment on the coarse time bin corresponding to one peak value, and when there are coarse time bins corresponding to M peaks, plus the first exposure time, a total of M+1 exposures are required. Specifically, during the second exposure time, the first storage space stores the first data, and compares the time box data output by the TDC in real time with the first data, where the initial value of the first data corresponds to the first peak value. Coarse time box, according to the comparison result, the first data is updated by adding or subtracting the preset adjustment difference, and the updated first data is the complete time box corresponding to the first peak; and so on, in the M+1 segment During the exposure time, the first storage space stores the Mth data, and compares the time bin data output by the TDC in real time with the Mth data, wherein the initial value of the Mth data is the coarse time box corresponding to the Mth peak, and according to the comparison result , the Mth data is updated by adding and subtracting the adjustment difference, and the updated Mth data is the complete time box corresponding to the Mth peak.

In the embodiment of the present application, when the coarse time box corresponding to each peak value is adjusted, the coarse time box will converge to the vicinity of the actual object distance measurement value after multiple comparisons of the real-time TDC output data.

For dTOF lidar, the corresponding statistical histogram satisfies the Poisson distribution. The values of these seemingly discrete statistical histograms are mostly concentrated around a fixed value, and this fixed value is the distance value corresponding to the object. From the statistical histogram, the position of the wave peak represents the distance corresponding to the object. . In the embodiment of the present application, the coarse time bin is continuously adjusted and updated through the real-time output data of the TDC, so that the final complete time bin is close to the value corresponding to the peak collected by the statistical histogram collection method. Specifically, the present application abandons the traditional statistical histogram statistical method, and does not need to record the data representing the measured distance of the object converted by each SPAD through TDC, but uses the coarse time bins corresponding to M peaks in different exposure time periods. For the real-time output data of the TDC, the coarse time bin corresponding to the peak value is compensated by adjusting the difference value, so that the coarse time bin converges to the vicinity of the actual object distance measurement value.

S50: Determine the distance measurement values of the M objects according to the complete time bins corresponding to the M peaks.

In one embodiment, after M+1 exposures, the coarse time bins corresponding to the M peaks are updated by adjusting the difference, so that the coarse time bins corresponding to the M peaks converge to the complete time bin. The peaks corresponding to the complete time bins can be considered equivalent to the peaks in the complete statistical histogram, so that the M object distance measurements can be determined. It should be understood that, when the laser ranging method of the present application is aimed at multi-target detection, the accuracy of the object distance measurement value of multi-target detection can still be maintained under the premise of using less storage capacity.

In steps S10-S50, a first storage space is provided, and the coarse time box corresponding to the peak value is converged by adjusting the difference value by performing numerical comparison between the coarse time box corresponding to the peak value in the first storage space and the data output by the TDC in real time. To make the coarse time box corresponding to the peak value closer to the actual object distance measurement value, after M+1 exposures, M object distance measurement values can be determined. The adjusted and updated complete time box has a small error with the actual object distance measurement value, and is basically equivalent to the actual object distance measurement value. The laser ranging method of the present application does not need to store complete statistical histogram data inside the ranging chip, which can effectively reduce the storage requirements, so that the area of the ranging chip can be significantly reduced, especially when detecting multi-target objects, it can still maintain more The accuracy of object distance measurements for target detection.

Further, in step S40, the time box data output by the TDC in real time is compared with the first data, the initial value of the first data is the coarse time box corresponding to the first peak value, and according to the comparison result, the first data is calculated by adding and subtracting The preset adjustment difference is updated, which includes the following steps:

S41: Compare the time bin data output by the TDC in real time with the first data, and if the first data is smaller than the time bin data output by the TDC in real time, add the first data and the adjustment difference to obtain the updated first data, which is stored in the first data. a storage space.

In one embodiment, the first data in the first storage space may be called PEAK_BIN, which indicates that the first data corresponds to a coarse time bin corresponding to the first peak in the histogram. Understandably, in the initial stage of comparing the time bin data output by TDC in real time with the first data in the first storage space, PEAK_BIN has not yet fully converged, and PEAK_BIN cannot accurately correspond to the peak value in the histogram. The number of comparisons increases until the end, and finally PEAK_BIN will be infinitely close to the object distance measurement value corresponding to the first peak value.

S42: If the first data is greater than the time box data output by the TDC in real time, the first data is subtracted from the adjustment difference to obtain updated first data, which is stored in the first storage space.

S43: If the first data is equal to the time box data output by the TDC in real time, the first data is reserved and stored in the first storage space.

In steps S41-S43, it can be expressed as: when TDCdata (time box data output by TDC in real time)>PEAK_BIN, PEAK_BIN(new)=PEAK_BIN(old)+delta; when TDCdata<PEAK_BIN, PEAK_BIN(new)=PEAK_BIN( old)-delta; when TDCdata=PEAK_BIN, PEAK_BIN remains unchanged, where PEAK_BIN(new) refers to the first data updated after the comparison, PEAK_BIN(old) refers to the first data during the comparison, and delta represents the adjustment difference . Understandably, the first data is a conceptual representation of the coarse time bin corresponding to the first peak in the second exposure time, and so on, the Mth data is for the M+1 exposure time in the Mth period. A conceptual representation of the coarse time bins corresponding to peaks. It can be understood that steps S41-S43 are specific embodiments of adjusting and updating the coarse time bin corresponding to the first peak value, and other embodiments of adjusting and updating the coarse time bin corresponding to the peak selected in the coarse histogram are similar to this. This will not be repeated here.

In steps S41-S43, the user can update the PEAK_BIN according to the comparison result between TDCdata and PEAK_BIN by adjusting the difference delta, so that the PEAK_BIN is closer to the timebin corresponding to the peak value in the statistical histogram after multiple updates, that is, closer to the actual value. object detection distance.

Further, the range of the adjustment difference is set according to the coarse time precision of the coarse histogram. When the coarse time precision is lower, the value of the adjustment difference will be larger. Among them, the range of the adjustment difference can be set between 0.5-3. The user can use a smaller adjustment difference to adjust and update the coarse time bin, so that the obtained complete time bin will be closer to the object detection distance corresponding to the peak value. In one embodiment, if the coarse time accuracy of the coarse histogram is set to be lower, it means that the error between the coarse time bin corresponding to the peak value and the actual object detection distance may be larger. As a result, the value of the adjustment difference can be appropriately increased.

Further, selecting M peaks in the rough histogram includes: sorting all peaks in the rough histogram according to the peak size, and selecting M peaks from large to small; or, by setting a peak threshold, selecting a value greater than the peak threshold M peaks of . Understandably, the coarse histogram may include more than M peaks, and some peaks may be considered as noise data. If the actual requirement of the user is to measure the distances of M objects, M peaks can be selected. Specifically, M peaks can be selected in descending order of the peaks. Alternatively, the user may select M peaks of interest that are greater than the peak threshold according to the set peak threshold, and analyze the object distances corresponding to these peaks of interest.

Further, the laser ranging method also includes:

S60: A second storage space is provided, and the storage capacity of the second storage space is larger than that of the first storage space.

In one embodiment, a second storage space may be provided to further improve the accuracy of the complete time bin by utilizing the historical data stored in the second storage space.

S70: During the second exposure time, store the first data in the first storage space, compare the time box data output by the TDC in real time with the first data, and the initial value of the first data is the rough time corresponding to the first peak value box, according to the comparison result, the first data is updated by adding and subtracting the adjustment difference value, and is stored in the second storage space at the same time. The storage capacity of the second storage space can store the historical values of N first data. During 1 exposure time, the Mth data is stored in the first storage space, and the time box data output by the TDC in real time is compared with the Mth data. The initial value of the Mth data is the coarse time box corresponding to the Mth peak. According to the comparison As a result, the Mth data is updated by adding and subtracting the adjustment difference, and is stored in the second storage space at the same time, and the storage capacity of the second storage space can store N historical values of the Mth data.

In one embodiment, the second storage space can store some of the newer PEAK_BINs that have just been updated and replaced, that is, it can be understood that the second storage space can store PEAK_BINs of N historical records.

Further, the second storage space is a shift register that supports storing N coarse time bins. In one embodiment, the characteristics of the shift register can be used to store the newly updated PEAK_BIN(new) as the first data in the first storage space after each update of the PEAK_BIN (taking the second exposure time as an example). , move the just updated PEAK_BIN(old) into the next storage space of the first storage space, and other storage parts of the second storage space are also shifted and replaced. When the second storage space is full, the earliest The N+1th PEAK_BIN stored will be removed. The first storage space stores the latest historical value of PEAK_BIN.

S80: Calculate the average value of the historical values of the N pieces of first data, and so on, calculate according to the exposure time period to obtain the average value of the historical values of the Mth data within the N Mth+1th exposure time.

S90: Determine the M object distance measurement values according to the average value of the historical values of the N first data and the average value of the historical values of the Mth data from the exposure time period to the N M+1th exposure times.

In steps S60-S90, the second storage space may store the historical values of the coarse time bins corresponding to the latest N peaks, that is, the value stored in the second storage space is the coarse time bins updated after the last N comparisons. In the embodiment of the present application, according to the average value of the historical values of N coarse time bins, the average value can be rounded to determine the object distance measurement value. In this way, compared with steps S10-S50, the complete coarse time obtained by the last update is used. The box method is more fault-tolerant, so that the determined M object distance measurements are closer to the actual object distance measurements.

Further, the first storage space is a first-in, first-out memory. Specifically, the first storage space may be SRAM. Using SRAM as the first storage space can support the storage of the above data.

Further, the laser ranging method also includes:

Acquire a preset interval range of peaks, then re-determine M peaks based on the M peaks according to the preset peak interval range, and finally acquire a corresponding complete time box according to the re-determined M peaks.

It can be understood that the peaks on the coarse histogram do not represent the peaks on the complete statistical histogram. In the selection of M peaks, points can be taken near the M peaks (limited within the preset interval range of each peak). , these points may be closer to the peak situation on the full statistical histogram, so that the full time bin obtained from the re-determined M peaks will be more accurate.

Further, the adjustment difference value includes a first adjustment difference value and a second adjustment difference value, the value of the first adjustment difference value is greater than the value of the second adjustment difference value, and the adjustment difference value is changed according to the number of times received by the TDC, wherein, when compared When the number of times reaches the preset threshold, the first adjustment difference is changed to the second adjustment difference.

In one embodiment, delta1 and delta2 are set, wherein the value of delta1 is greater than the value of delta2. In the initial stage of the value comparison, in order to quickly converge the coarse time box corresponding to the peak value, delta1 with a larger value can be used. In the middle or later stage of the comparison, in order for the first data to converge more stably and approach the actual object detection distance, a smaller value delta2 can be used, which can further improve the efficiency of updating the first data, and make the peak corresponding to the The gap between the time bin and the actual object detection distance is smaller. The preset threshold can be determined according to the number of comparisons. For example, the preset threshold is 1/5 or 1/4 of the total number of comparisons, that is, in the first 1/5 or 1/4 stage of the comparison, a larger value delta1 is used, In later stages, a smaller value of delta2 is used. Further, the range of the adjustment difference is 0.5-3, for example, delta1 is specifically set to 2, and delta2 is specifically set to 1.

Compared with the ranging method in the prior art, the laser ranging method of the present application includes but is not limited to the following advantages:

There is no need to store complete statistical histogram data inside the chip, and the chip area can be significantly reduced; while the chip area is reduced, the power consumption and cost of the chip are significantly reduced; The method of adjusting the difference to update the coarse time box can realize the calculation of data addition or subtraction in one shot, thereby improving the data processing speed of the entire TDC module; since the statistical histogram is no longer used to calculate the depth value , but the chip directly outputs the depth data (timebin value), so the data output of the chip and the amount of post-stage operations of the statistical histogram (such as matched filtering + peak-finding algorithm, etc.) will be significantly reduced, which can improve the processing of the chip. efficiency.

In the embodiment of the present application, a first storage space is provided. During the first period of exposure time, the trigger times of the TDC output are stored and accumulated in the first storage space to generate a coarse histogram corresponding to the coarse time accuracy. The method of histogram can reduce the storage requirement, and can roughly describe the data situation of the complete histogram; then select M peaks in the coarse histogram, and obtain the coarse time bins corresponding to the M peaks, which can further reduce the storage. Requirement, select the coarse time bins with peak characteristics from the coarse histogram to quickly determine the coarse time bins related to the object distance measurement value when performing distance detection on multi-target objects; then obtain the coarse time bins corresponding to the M peaks. The complete time bins corresponding to the M peaks, after positioning the coarse time bins, on the basis of the coarse time bins, the coarse time bins corresponding to the peak values are continuously updated and adjusted through each numerical comparison, so that the coarse time bins are at the initial value At the same time, it quickly converges to the vicinity of the actual object distance measurement value, and obtains a complete time box that can accurately reflect the object distance detection; finally, according to the complete time box corresponding to the M peaks, the M object distance measurement values are determined. Using the laser ranging method does not need to save all the histogram data, which can significantly reduce the area of the ranging chip.

It should be understood that the size of the sequence numbers of the steps in the above embodiments does not mean the sequence of execution, and the execution sequence of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

Embodiments of the present application provide a laser ranging device. The laser ranging device includes:

Laser transmitter for emitting laser light;

SPAD array for receiving optical signals;

TDC arrays for converting the time-of-flight of optical signals into digital signals;

The coarse histogram control circuit is used for storing and accumulating the trigger times of the TDC output in the first storage space during the first exposure time, to generate a coarse histogram corresponding to the coarse time precision; and for selecting in the coarse histogram M peaks, obtain the coarse time bins corresponding to the M peaks;

a memory for storing the coarse time bins corresponding to the M peaks in the coarse histogram;

The complete time bin adjustment control circuit is used to obtain the complete time bins corresponding to the M peaks according to the coarse time bins corresponding to the M peaks, and specifically includes: during the second exposure time, storing the first data in the first storage space, The time bin data output by the TDC in real time is compared with the first data. The initial value of the first data is the coarse time bin corresponding to the first peak value. According to the comparison result, the first data is updated by adding and subtracting the preset adjustment difference. The updated first data is the complete time box corresponding to the first peak value. During the exposure time of the M+1th segment, the Mth data is stored in the first storage space, and the time box data output by the TDC in real time is compared with the Mth data. For comparison, the initial value of the Mth data is the coarse time box corresponding to the Mth peak. According to the comparison result, the Mth data is updated by adding and subtracting the adjustment difference, and the updated Mth data is the complete time corresponding to the Mth peak. box;

The readout circuit is used for determining the distance measurement values of the M objects according to the complete time bins corresponding to the M peaks.

The laser ranging device further includes a second storage space and a computing unit, wherein the storage capacity of the second storage space is larger than that of the first storage space;

The complete time box adjustment control circuit is further configured to store the first data in the first storage space during the second exposure time period, and compare the time box data output by the TDC in real time with the first data , the initial value of the first data is the coarse time box corresponding to the first peak value, and according to the comparison result, the first data is updated by adding and subtracting the adjustment difference, and is stored in the In the second storage space, the storage capacity of the second storage space can store N historical values of the first data, and within the exposure time of the M+1th segment, the Mth data is stored in the first storage space, Compare the time box data output by TDC in real time with the Mth data, the initial value of the Mth data is the coarse time box corresponding to the Mth peak, and according to the comparison result, the Mth data passes through. Adding and subtracting the adjustment difference to complete the update, and simultaneously saving it in the second storage space, the storage capacity of the second storage space can store N historical values of the Mth data;

The calculation unit is used to calculate the average value of the historical values of the N first data, and so on, according to the exposure time period, to obtain the history of the Mth data within the Nth M+1 exposure time. the average of the values;

The readout circuit is further configured to calculate the average value of the historical values of the Mth data according to the average value of the historical values of the N pieces of the first data and the average value of the historical values of the Mth data according to the exposure time period to the Nth M+1th exposure time value to determine M distance measurements of the object.

In the embodiment of the present application, a first storage space is provided. During the first period of exposure time, the trigger times of the TDC output are stored and accumulated in the first storage space to generate a coarse histogram corresponding to the coarse time accuracy. The histogram method can reduce storage requirements and roughly describe the data situation of the complete histogram; then select M peaks in the coarse histogram, and obtain the coarse time bins corresponding to the M peaks, which can further reduce storage. Requirement, select the coarse time bins with peak characteristics from the coarse histogram to quickly determine the coarse time bins related to the distance measurement value of the objects when performing distance detection on multi-target objects; then obtain the coarse time bins corresponding to the M peaks. The complete time bins corresponding to the M peaks, after the coarse time bins are located, on the basis of the coarse time bins, the coarse time bins corresponding to the peak values are continuously updated and adjusted through each numerical comparison, so that the coarse time bins are at the initial value At the same time, it quickly converges to the vicinity of the actual object distance measurement value, and obtains a complete time box that can accurately reflect the object distance detection; finally, according to the complete time box corresponding to the M peaks, the M object distance measurement values are determined. Using the laser ranging method does not need to save all the histogram data, which can significantly reduce the area of the ranging chip.

Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. Module completion means dividing the internal structure of the device into different functional units or modules to complete all or part of the functions described above.

The above embodiments are only used to illustrate the technical solutions of the present application, but not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: The recorded technical solutions are modified, or some technical features thereof are equivalently replaced; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the application, and should be included in the application. within the scope of protection.

Claims (10)

1. a laser ranging method, is characterized in that, comprises: There is a first storage space; During the first exposure time, the trigger times of the TDC output are stored and accumulated in the first storage space to generate a coarse histogram corresponding to the coarse time accuracy; Select M peaks in the coarse histogram, and obtain the coarse time bins corresponding to the M peaks; Acquiring the complete time bins corresponding to the M peaks according to the coarse time bins corresponding to the M peaks specifically includes: storing the first data in the first storage space during the second exposure period, storing the TDC The real-time output time bin data is compared with the first data. The initial value of the first data is the coarse time bin corresponding to the first peak value. According to the comparison result, the first data is calculated by adding and subtracting The preset adjustment difference is updated, and the updated first data is the complete time box corresponding to the first peak value. During the exposure time of the M+1th segment, in the first storage The Mth data is stored in the space, and the time box data output by the TDC in real time is compared with the Mth data. The initial value of the Mth data is the coarse time box corresponding to the Mth peak. According to the comparison result, The Mth data is updated by adding and subtracting the adjustment difference, and the updated Mth data is the complete time box corresponding to the Mth peak; M objects distance measurements are determined according to the complete time bins corresponding to the M peaks. 2 . The method according to claim 1 , wherein the time bin data output by the TDC in real time is compared with the first data, and the initial value of the first data corresponds to the first peak value. 3 . The coarse time box of , according to the comparison result, the first data is updated by adding and subtracting a preset adjustment difference, including: Compare the time box data output by the TDC in real time with the first data, and if the first data is smaller than the time box data output by the TDC in real time, then the first data plus the adjustment difference is obtained. The updated first data is stored in the first storage space; If the first data is greater than the time box data output by the TDC in real time, the first data is subtracted from the adjustment difference to obtain the updated first data, which is stored in the first storage space ; If the first data is equal to the time box data output by the TDC in real time, the first data is reserved and stored in the first storage space. 3 . The method according to claim 1 , wherein the range of the adjusted difference value is set according to the coarse time accuracy of the coarse histogram, and when the coarse time accuracy is lower, the difference value is adjusted. 4 . will be larger. 4. The method according to claim 1, wherein the selecting M peaks in the rough histogram comprises: sorting all peaks in the rough histogram according to the peak size, from large to small , select M peaks; or, by setting a peak threshold, select M peaks greater than the peak threshold. 5. The method according to claim 1, wherein the method further comprises: A second storage space is provided, and the storage capacity of the second storage space is larger than that of the first storage space; During the second exposure time, the first data is stored in the first storage space, and the time box data output by the TDC in real time is compared with the first data. The initial value of the first data is the first Each of the coarse time bins corresponding to the peak values, according to the comparison result, the first data is updated by adding and subtracting the adjustment difference, and is stored in the second storage space at the same time. The storage capacity can store N historical values of the first data. During the exposure time of the M+1th segment, the Mth data is stored in the first storage space, and the time box data output by the TDC in real time and the M data are compared, the initial value of the M th data is the coarse time bin corresponding to the M th peak, and according to the comparison result, the M th data is updated by adding and subtracting the adjustment difference, and at the same time Stored in the second storage space, the storage capacity of the second storage space can store N historical values of the Mth data; Calculate the average value of the historical value of the N described first data, and so on, according to the exposure time period, calculate to obtain the average value of the historical value of the Mth data within the Nth M+1 exposure time; According to the average value of the historical values of the N pieces of the first data and the average value of the historical values of the Mth data from the exposure time period to the N M+1th exposure times, the M distances of the objects are determined Measurements. 6. The method according to claim 1, wherein the first storage space is a first-in, first-out memory. 7. The method of claim 1, wherein the method further comprises: Get the peak preset interval range; According to the preset interval range of the peaks, re-determining the M peaks on the basis of the M peaks; The corresponding complete time bins are acquired according to the re-determined M peaks. 8. The method according to any one of claims 1-7, wherein the adjustment difference value comprises a first adjustment difference value and a second adjustment difference value, and the value of the first adjustment difference value is greater than the The value of the second adjustment difference, the adjustment difference is changed according to the number of times of receiving the TDC, wherein when the number of comparisons reaches a preset threshold, the first adjustment difference is changed to the second adjustment difference . 9. A laser ranging device, comprising: Laser transmitter for emitting laser light; SPAD array for receiving optical signals; TDC arrays for converting the time-of-flight of optical signals into digital signals; The coarse histogram control circuit is used for storing and accumulating the trigger times of the TDC output in the first storage space during the first exposure time, so as to generate a coarse histogram corresponding to the coarse time precision; Select M peaks in the histogram, and obtain the coarse time bins corresponding to the M peaks; a memory for storing the coarse time bins corresponding to the M peaks in the coarse histogram; A complete time bin adjustment control circuit, configured to obtain the complete time bins corresponding to the M peaks according to the coarse time bins corresponding to the M peaks, specifically including: during the second exposure time period, in the first exposure time The storage space stores the first data, and compares the time bin data output by the TDC in real time with the first data. The initial value of the first data is the coarse time bin corresponding to the first peak value. According to the comparison result , the first data is updated by adding and subtracting a preset adjustment difference, and the updated first data is the complete time box corresponding to the first peak value, and is exposed in the M+1 segment During the time, the Mth data is stored in the first storage space, and the time box data output by the TDC in real time is compared with the Mth data, and the initial value of the Mth data is the Mth corresponding to the peak value. For the coarse time box, according to the comparison result, the Mth data is updated by adding and subtracting the adjustment difference, and the updated Mth data is the complete time box corresponding to the Mth peak; A readout circuit, configured to determine M distance measurement values of objects according to the complete time bins corresponding to the M peaks. 10. The apparatus according to claim 9, further comprising a second storage space and a computing unit, wherein the storage capacity of the second storage space is larger than that of the first storage space; The complete time box adjustment control circuit is further configured to store the first data in the first storage space during the second exposure time period, and compare the time box data output by the TDC in real time with the first data , the initial value of the first data is the coarse time box corresponding to the first peak value, and according to the comparison result, the first data is updated by adding and subtracting the adjustment difference, and is stored in the In the second storage space, the storage capacity of the second storage space can store N historical values of the first data, and within the exposure time of the M+1th segment, the Mth data is stored in the first storage space, Compare the time box data output by TDC in real time with the Mth data, the initial value of the Mth data is the coarse time box corresponding to the Mth peak, and according to the comparison result, the Mth data passes through. Adding and subtracting the adjustment difference to complete the update, and simultaneously saving it in the second storage space, the storage capacity of the second storage space can store N historical values of the Mth data; The calculation unit is used to calculate the average value of the historical values of the N first data, and so on, according to the exposure time period, to obtain the history of the Mth data within the Nth M+1 exposure time. the average of the values; The readout circuit is further configured to calculate the average value of the historical values of the Mth data according to the average value of the historical values of the N pieces of the first data and the average value of the historical values of the Mth data according to the exposure time period to the Nth M+1th exposure time value to determine M distance measurements of the object.

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