[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

CN111948608B - Underwater sound multipath signal arrival time difference estimation method based on sparse modeling - Google Patents

Underwater sound multipath signal arrival time difference estimation method based on sparse modeling Download PDF

Info

Publication number
CN111948608B
CN111948608B CN202010816503.1A CN202010816503A CN111948608B CN 111948608 B CN111948608 B CN 111948608B CN 202010816503 A CN202010816503 A CN 202010816503A CN 111948608 B CN111948608 B CN 111948608B
Authority
CN
China
Prior art keywords
time
signal
time difference
underwater
sparse
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202010816503.1A
Other languages
Chinese (zh)
Other versions
CN111948608A (en
Inventor
张贞凯
江峰
林云航
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Suzhou High Airlines Intellectual Property Rights Operation Co ltd
Yunnan Poly Tiantong Underwater Equipment Technology Co ltd
Original Assignee
Jiangsu University of Science and Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Jiangsu University of Science and Technology filed Critical Jiangsu University of Science and Technology
Priority to CN202010816503.1A priority Critical patent/CN111948608B/en
Publication of CN111948608A publication Critical patent/CN111948608A/en
Application granted granted Critical
Publication of CN111948608B publication Critical patent/CN111948608B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/18—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using ultrasonic, sonic, or infrasonic waves
    • G01S5/22—Position of source determined by co-ordinating a plurality of position lines defined by path-difference measurements

Landscapes

  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Measurement Of Velocity Or Position Using Acoustic Or Ultrasonic Waves (AREA)

Abstract

本发明公开了一种基于稀疏建模的水声多径信号到达时间差的估计方法，包括如下步骤：(1)水下目标通过发送声波信号传递至参考传感器和其他传感器，其中传感器接收的声波信号中含有海面反射和曲线传播等的非视距时延信息；(2)对参考传感器接收的信号进行时间反转处理，将时间反转后的信号与其余传感器接收的信号分别做卷积运算，再对卷积后的所有信号做离散傅里叶变换；(3)采样时间对称扩展到负半轴并将其细化，使得零时刻到最大采样时间这段时间区间扩展到负半轴。利用细化的采样时间对所得信号进行稀疏重构，并用正交匹配追踪方法提取出稀疏信号的所有时间差参数，提取的时间差参数应用于TDOA定位。

Figure 202010816503

The invention discloses a method for estimating the time difference of arrival of underwater acoustic multipath signals based on sparse modeling, comprising the following steps: (1) the underwater target transmits the acoustic wave signal to the reference sensor and other sensors, wherein the acoustic wave signal received by the sensor It contains non-line-of-sight delay information such as sea surface reflection and curve propagation; (2) Perform time-reversal processing on the signal received by the reference sensor, and convolve the time-reversed signal with the signals received by the other sensors respectively, Then perform discrete Fourier transform on all the convolved signals; (3) the sampling time is symmetrically extended to the negative semi-axis and refined, so that the time interval from the zero time to the maximum sampling time is extended to the negative semi-axis. The obtained signal is sparsely reconstructed using the refined sampling time, and all the time difference parameters of the sparse signal are extracted by the orthogonal matching pursuit method, and the extracted time difference parameters are used for TDOA positioning.

Figure 202010816503

Description

Underwater sound multipath signal arrival time difference estimation method based on sparse modeling
Technical Field
The invention belongs to the field of underwater sound source positioning, and particularly relates to an underwater sound multipath signal arrival time difference estimation method based on sparse modeling.
Background
The underwater sound source positioning is a key technology of an underwater wireless sensor network, and is a guarantee for long-time underwater operation of an autonomous underwater vehicle, an unmanned underwater vehicle and the like.
In complex marine environments, underwater acoustic signals are often accompanied by severe noise interference and multipath effects, which make positioning underwater sound sources difficult. The positioning of the time difference of arrival has the advantages of high complexity, low positioning requirement and the like, thereby becoming a main method for positioning the underwater sound source. The time difference of arrival parameter extracted from the underwater acoustic signal becomes the first problem of positioning, and the most common time difference of arrival estimation method is a mutual fuzzy function. The mutual ambiguity function can quickly solve the time difference of arrival parameters of the signals, but the precision is greatly reduced under the condition of high noise.
Disclosure of Invention
The purpose of the invention is as follows: the invention aims to provide an underwater acoustic multipath signal arrival time difference estimation method based on sparse modeling, which is used for solving the problems.
The technical scheme is as follows: the invention relates to an underwater acoustic multipath signal arrival time difference estimation method based on sparse modeling, which comprises the following steps of:
(1) the underwater target transmits the acoustic signals to the reference sensor and other sensors;
(2) carrying out time reversal processing on signals received by a reference sensor, carrying out convolution operation on the signals subjected to time reversal and signals received by other sensors respectively, and carrying out discrete Fourier transform on all the signals subjected to convolution;
(3) the sampling time is symmetrically expanded to a negative half shaft and then refined, sparse reconstruction is carried out on the obtained signals by utilizing the refined sampling time, all time difference parameters of the sparse signals are extracted by an orthogonal matching tracking method, and the extracted time difference parameters are applied to TDOA positioning.
Further, in step (1), the sensor receives signals as follows
When the underwater target transmits a carrier wave s (t), the underwater acoustic signal received by the sensor i (i ═ 1,2, …, N) is as follows
Figure BDA0002632927200000011
In the formula betai,kFor the gain of the kth path, τi,kIs the time delay of the kth path, K is the number of multipaths, wi(t) is a noise function;
the number of the sensors is N +1, the sensor 0 is a reference sensor, and the sound wave signal received by the reference sensor is expressed as
Figure BDA0002632927200000021
In the formula beta0,dIs the gain, τ, of the d-th path0,dTime delay of the D-th path, D is the number of multipaths, w0(t) is a noise function.
Further, in step (2), the time reversal of the underwater acoustic signal is as follows
For y0Is processed by time reversal to obtain
Figure BDA0002632927200000022
Where represents the convolution operation, δ (t) is the unit impulse function,
for acoustic signal yiAnd y'0Is obtained by convolution operation
Figure BDA0002632927200000023
Wherein w (t) is a noise function obtained by discrete Fourier transform of equation (4)
Figure BDA0002632927200000024
Wherein M is 0,1, …, M-1, M is the number of sampling points, fcIs the carrier frequency, Δ f is the sampling interval, W (m) is the discrete Fourier transform of w (t), where the discrete Fourier transform of s (t) is S (m).
Further, in step (3), the sampling time is refined as follows
The sampling time of the signal is p, and the sampling time is thinned
Figure BDA0002632927200000025
Wherein n is a positive integer greater than ten thousand, such that
Figure BDA0002632927200000026
Sufficiently small and n is much greater than KD;
Figure BDA0002632927200000027
representing contained relationships between collections.
Further, in step (3), the sparse reconstruction of the signal is as follows
By equation (6), constructing a sparse matrix is written as
Figure BDA0002632927200000031
Where E' is an M × (2n +1) -dimensional matrix, the matrix equation is thus represented as
Y＝SE′B′+W＝θB′+W (8)
In the formula
Y＝[Yi,0(0),Yi,0(1),…,Yi,0(M-1)]T (9)
S＝diag([S(0)S(0),…,S(M-1)S(-M+1)]) (10)
Figure BDA0002632927200000032
W＝[W(0),W(1),…,W(M-1)]T (12)
θ is an unknown quantity SE 'and B'; equation (8) is solved by an orthogonal matching pursuit algorithm, β2n+1Is the amplitude of the virtual path, the number of lines of B' corresponds to the set of delay differences
Figure BDA0002632927200000033
Set the row number and time difference of all non-zero terms of B
Figure BDA0002632927200000034
One-to-one correspondence, the first row of B' corresponds to the time difference-p; the extracted time difference parameter is multiplied by the TDOA measured value required by the underwater sound velocity to determine the positioning.
Has the advantages that: the method for estimating the arrival time difference of the underwater acoustic multipath signals based on sparse modeling can effectively solve the problem of estimation of the arrival time difference of the multipath signals in underwater sound source positioning, and has the advantages of high complexity and high precision.
Drawings
FIG. 1 is a graph of acoustic propagation of an underwater target;
FIG. 2 is a block diagram of underwater multipath signal time difference of arrival estimation;
FIG. 3 an underwater acoustic signal;
Detailed Description
As shown in fig. 1 to 3, the target transmits acoustic waves to the plurality of sensors, and the acoustic signals may be multipath signals of straight line propagation, curved line propagation, sea surface reflection, or the like. The invention discloses an underwater acoustic multipath signal arrival time difference estimation method based on sparse modeling, which comprises the following steps of:
(1) the underwater target transmits the acoustic signals to a reference sensor and other sensors by sending the acoustic signals, wherein the acoustic signals received by the sensors contain non-line-of-sight time delay information such as sea surface reflection, curve propagation and the like;
(2) carrying out time reversal processing on signals received by a reference sensor, carrying out convolution operation on the signals subjected to time reversal and signals received by other sensors respectively, and carrying out discrete Fourier transform on all the signals subjected to convolution;
(3) the sampling time is symmetrically extended to the negative half axis and thinned such that the time interval from zero to the maximum sampling time is extended to the negative half axis. And carrying out sparse reconstruction on the obtained signal by utilizing the thinned sampling time, extracting all time difference parameters of the sparse signal by using an orthogonal matching tracking method, and applying the extracted time difference parameters to TDOA positioning.
Further, in the step (1), the sensor receives the signal as follows
When the underwater target transmits a carrier wave s (t), the underwater acoustic signal received by the sensor i (i ═ 1,2, …, N) is as follows
Figure BDA0002632927200000041
In the formula betai,kFor the gain of the kth path, τi,kIs the time delay of the kth path, K is the number of multipaths, wi(t) is a noise function;
the number of the sensors is N +1, the sensor 0 is a reference sensor, and the sound wave signal received by the reference sensor is expressed as
Figure BDA0002632927200000042
In the formula beta0,dIs the gain, τ, of the d-th path0，dTime delay of the D-th path, D is the number of multipaths, w0(t) is a noise function.
Equations (1) and (2) are rewritten as
Figure BDA0002632927200000043
Figure BDA0002632927200000044
Where represents the convolution operation and δ (t) is the unit impulse function.
Further, in the step (2), for y0Is processed by time reversal to obtain
Figure BDA0002632927200000045
For acoustic signal yiAnd y'0Is obtained by convolution operation
Figure BDA0002632927200000051
Where w (t) is a noise function obtained by discrete Fourier transform of equation (6)
Figure BDA0002632927200000052
Wherein M is 0,1, …, M-1, M is the number of sampling points, fcIs the carrier frequency, Δ f is the sampling interval, W (m) is the discrete Fourier transform of w (t), where the discrete Fourier transform of s (t) is S (m).
Further, in step (3), the thinning of the sampling time and the sparse reconstruction of the signal are as follows
Equation (7) of step (2) is written in the form of a matrix as follows
Y＝SEB+W (8)
In the formula
Y＝[Yi,0(0)，Yi，0(1),…,Yi,0(M-1)]T (9)
S＝diag([S(0)S(0),…,S(M-1)S(-M+1)]) (10)
Figure BDA0002632927200000053
Figure BDA0002632927200000054
W＝[W(0),W(1),…,W(M-1)]T (13)
Where matrix E is an M by KD dimensional matrix and vector B has dimension KD.
From the matrix equation, both equations (11) and (12) contain delay parameters, so that sparse reconstruction of equation (11) is required. The sampling time of the signal is p, the sampling time is thinned, and the result is shown as follows
Figure BDA0002632927200000055
Where n is a positive integer large enough (n is generally greater than ten thousand, the larger n the more accurate the time difference estimate, but the system load will also increase) so that
Figure BDA0002632927200000056
Sufficiently small and n is much greater than KD;
Figure BDA0002632927200000057
representing contained relationships between collections; here, it is considered to reverse the time such that the time interval from the zero time to the maximum sampling time extends to the negative half-axis.
By equation (14), the matrix E is thinned out, and the thinned matrix is written as
Figure BDA0002632927200000061
Where E' is an M × (2n +1) -dimensional matrix, the new matrix equation is thus expressed as
Y＝SE′B′+W＝θB′+W (16)
In the formula
Figure BDA0002632927200000062
θ is an unknown quantity SE 'and B'.
Equation (16) is solved by an orthogonal matching pursuit algorithm, β2n+1Is the amplitude of the virtual path, the number of lines of B' corresponds to the set of delay differences
Figure BDA0002632927200000063
Set the row number and time difference of all non-zero terms of B
Figure BDA0002632927200000064
One-to-one correspondence, the first row of B' corresponds to the time difference-p; the extracted time difference parameter multiplied by the underwater sound velocity is the TDOA measurement required for positioning.

Claims (1)

1.基于稀疏建模的水声多径信号到达时间差的估计方法，其特征在于，包括以下步骤：1. the estimation method of the time difference of arrival of underwater acoustic multipath signals based on sparse modeling, is characterized in that, comprises the following steps: (1)水下目标通过发送声波信号传递至参考传感器和其他传感器，所述参考传感器和其他传感器接收信号如下(1) The underwater target is transmitted to the reference sensor and other sensors by sending acoustic wave signals, and the reference sensor and other sensors receive signals as follows 当水下目标发射的载波为s(t)时，传感器i＝1,2,…,N接收的水声信号如下When the carrier wave emitted by the underwater target is s(t), the underwater acoustic signal received by the sensor i=1,2,...,N is as follows
Figure FDA0002913603440000011
Figure FDA0002913603440000011
 式中βi,k为第k条径的增益，τi,k为第k条径的时延，K为多径数，wi(t)是噪声函数；where β i,k is the gain of the kth path, τ i,k is the time delay of the kth path, K is the multipath number, and w i (t) is the noise function; 传感器的个数为N+1，传感器0是参考传感器，参考传感器接收的声波信号表示为The number of sensors is N+1, sensor 0 is the reference sensor, and the acoustic signal received by the reference sensor is expressed as
Figure FDA0002913603440000012
Figure FDA0002913603440000012
 式中β0,d是第d条径的增益，τ0,d为第d条径的时延，D为多径数，w0(t)是噪声函数；where β 0,d is the gain of the d-th path, τ 0,d is the time delay of the d-th path, D is the multipath number, and w 0 (t) is the noise function; (2)对参考传感器接收的信号进行时间反转处理，将时间反转后的信号与其余传感器接收的信号分别做卷积运算，再对卷积后的所有信号做离散傅里叶；(2) Perform time-reversal processing on the signal received by the reference sensor, perform convolution operation on the time-reversed signal and the signals received by the other sensors, and then perform discrete Fourier on all the convolved signals; 对水声信号的时间反转如下The time reversal of the hydroacoustic signal is as follows 对y0进行时间反转处理得到The time reversal process is performed on y 0 to get
Figure FDA0002913603440000013
Figure FDA0002913603440000013
 式中*代表卷积操作，δ(t)为单位冲激函数，where * represents the convolution operation, δ(t) is the unit impulse function, 对声波信号yi和y′0做卷积运算得到The convolution operation is performed on the acoustic signal y i and y′ 0 to get
Figure FDA0002913603440000014
Figure FDA0002913603440000014
 式中w(t)是噪声函数，对方程(4)做离散傅里叶变换得到where w(t) is the noise function, and the discrete Fourier transform of equation (4) is obtained
Figure FDA0002913603440000015
Figure FDA0002913603440000015
 式中m的取值范围为m＝0,1,…,M-1，M为采样点数，fc是载波频率，Δf是采样间隔，W(m)是w(t)的离散傅里叶变换，这里s(t)的离散傅里叶变换是S(m)；In the formula, the value range of m is m=0,1,...,M-1, M is the number of sampling points, f c is the carrier frequency, Δf is the sampling interval, and W(m) is the discrete Fourier of w(t). Transform, where the discrete Fourier transform of s(t) is S(m); (3)采样时间先对称扩展到负半轴然后进行细化处理，利用细化的采样时间对所得信号进行稀疏重构，并用正交匹配追踪方法提取出稀疏信号的所有时间差参数，提取的时间差参数应用于TDOA定位；(3) The sampling time is first symmetrically extended to the negative semi-axis and then refined, and the obtained signal is sparsely reconstructed using the refined sampling time, and all the time difference parameters of the sparse signal are extracted by the orthogonal matching pursuit method. The extracted time difference The parameters are applied to TDOA positioning; 信号的采样时间为p，对采样时间进行细化：The sampling time of the signal is p, and the sampling time is refined:
Figure FDA0002913603440000021
Figure FDA0002913603440000021
 式中n为大于一万的正整数，使得
Figure FDA0002913603440000022
足够小和n远大于KD；
Figure FDA0002913603440000023
表示集合之间的被包含关系；where n is a positive integer greater than ten thousand, such that
Figure FDA0002913603440000022
is small enough and n is much larger than KD;
Figure FDA0002913603440000023
Represents a contained relationship between sets; 信号的稀疏重构如下The sparse reconstruction of the signal is as follows 通过方程(6)，构造稀疏化矩阵写为By Equation (6), the sparse matrix is constructed as
Figure FDA0002913603440000024
Figure FDA0002913603440000024
 式中E′是一个M×(2n+1)维矩阵，因此，矩阵方程表示为where E′ is an M×(2n+1) dimensional matrix, therefore, the matrix equation is expressed as Y＝SE′B′+W＝θB′+W (8)Y=SE′B′+W=θB′+W (8) 式中in the formula Y＝[Yi,0(0),Yi,0(1),…,Yi,0(M-1)]T (9)Y=[Y i,0 (0),Y i,0 (1),...,Y i,0 (M-1)] T (9) S＝diag([S(0)S(0),…,S(M-1)S(-M+1)]) (10)S=diag([S(0)S(0),...,S(M-1)S(-M+1)]) (10)
Figure FDA0002913603440000025
Figure FDA0002913603440000025
 W＝[W(0),W(1),…,W(M-1)]T (12)W=[W(0),W(1),...,W(M-1)] T (12) θ＝SE′和B′是一个未知量；方程(8)通过正交匹配追踪算法来求解，β2n+1是虚拟径的幅值，B′的行数对应时延差集合
Figure FDA0002913603440000026
将B′所有不为零的项的行数与时间差集合
Figure FDA0002913603440000027
一一对应，B′的第一行对应时间差-p；提取出的时间差参数乘以水下声速确定定位所需的TDOA测量值。θ=SE′ and B′ are an unknown quantity; Equation (8) is solved by the orthogonal matching pursuit algorithm, β 2n+1 is the amplitude of the virtual radius, and the number of rows of B′ corresponds to the delay difference set
Figure FDA0002913603440000026
Set the row count and time difference of all non-zero items of B'
Figure FDA0002913603440000027
One-to-one correspondence, the first line of B' corresponds to the time difference -p; the extracted time difference parameter is multiplied by the underwater sound speed to determine the TDOA measurement value required for positioning.
CN202010816503.1A 2020-08-14 2020-08-14 Underwater sound multipath signal arrival time difference estimation method based on sparse modeling Active CN111948608B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010816503.1A CN111948608B (en) 2020-08-14 2020-08-14 Underwater sound multipath signal arrival time difference estimation method based on sparse modeling

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010816503.1A CN111948608B (en) 2020-08-14 2020-08-14 Underwater sound multipath signal arrival time difference estimation method based on sparse modeling

Publications (2)

Publication Number Publication Date
CN111948608A CN111948608A (en) 2020-11-17
CN111948608B true CN111948608B (en) 2021-03-19

Family

ID=73343358

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010816503.1A Active CN111948608B (en) 2020-08-14 2020-08-14 Underwater sound multipath signal arrival time difference estimation method based on sparse modeling

Country Status (1)

Country Link
CN (1) CN111948608B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114325131B (en) * 2021-12-30 2024-12-17 西安交通大学 Directional radiation source positioning method combined with time difference method and time inversion technology

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103076604B (en) * 2012-12-31 2015-03-04 东南大学 Method for measuring distance of low-frequency underwater sound pulse signal on basis of frequency dispersion features
CN103176166B (en) * 2013-03-14 2015-03-04 东南大学 Tracking algorithm for time difference of arrival of signals for acoustic passive positioning
CN103442435B (en) * 2013-08-21 2016-03-23 天津大学 A kind of method improving location coverage in underwater sound 3D sensor network
CN103472457B (en) * 2013-09-13 2015-06-10 中国科学院空间科学与应用研究中心 Three-dimensional imaging system and method for calculating correlation flight time by means of sparse aperture compression
CN104780128B (en) * 2015-04-14 2019-05-21 哈尔滨工程大学 A kind of estimation of underwater sound OFDMA uplink communication condition of sparse channel and pilot frequency optimization method
CN105068048B (en) * 2015-08-14 2016-10-19 南京信息工程大学 Sound source localization method of distributed microphone array based on spatial sparsity
CN108387867A (en) * 2018-02-09 2018-08-10 华南理工大学 A kind of underwater source node localization method
CN110113286B (en) * 2019-05-06 2020-06-26 厦门大学 A Low-Complexity Underwater Acoustic Channel Estimation Algorithm Based on Orthogonal Matching Pursuit
CN111555994B (en) * 2020-05-22 2021-04-02 西北工业大学 A Cluster Sparse Channel Estimation Method Based on the Maximum Skip Line Criterion Algorithm

Also Published As

Publication number Publication date
CN111948608A (en) 2020-11-17

Similar Documents

Publication Publication Date Title
CN109541568B (en) Radar maneuvering target cross-range and Doppler unit fast coherent accumulation detection method
CN108089155B (en) A passive localization method of single hydrophone sound source in deep sea environment
CN108802683B (en) A source localization method based on sparse Bayesian learning
CN103176166B (en) Tracking algorithm for time difference of arrival of signals for acoustic passive positioning
CN109164438A (en) A kind of combined estimation method of arrival time and arrival rate based on LFM coherent pulse string
CN112346014B (en) A positioning method of multistatic sonar based on signal arrival time difference
Gerstoft et al. Adaptive beamforming of a towed array during a turn
CN109633622A (en) Across the unit accumulation method of radar maneuvering target based on time reversal second order Keystone transformation
Yang et al. Moving target localization in multistatic sonar using time delays, Doppler shifts and arrival angles
CN111948608B (en) Underwater sound multipath signal arrival time difference estimation method based on sparse modeling
Gu et al. Using McDaniel's model to represent non-Rayleigh reverberation
Saqib et al. Sound-based distance estimation for indoor navigation in the presence of ego noise
CN112924926B (en) A DOA Estimation Method for Multiple Channels
CN111856400B (en) Underwater target sound source positioning method and system
CN108761384A (en) A kind of sensor network target localization method of robust
CN117805733A (en) A deep-sea broadband sound source positioning method, device and equipment using a single hydrophone
CN113126029B (en) A multi-sensor pulsed sound source localization method suitable for deep-sea reliable sound path environment
CN113589297B (en) Target speed estimation method by jointly utilizing transmitting and receiving combined echo and transmitting and receiving separated echo
JP7397383B2 (en) Doppler compensation system and Doppler compensation method
CN109270344B (en) Coherent pulse signal frequency estimation method under pulse loss
CN111190173B (en) Phased array radar target tracking method based on predicted value measurement conversion
CN116359893B (en) A matching field underwater sound source localization method suitable for non-synchronous arrays
CN110244261A (en) Method, system, device and storage medium for estimating ultra-short baseline orientation of arbitrary formation
CN114910864B (en) Multi-platform Doppler positioning method with unknown signal propagation speed and signal frequency drift
CN117368925B (en) Deep sea underwater sound target distance estimation method based on graph Fourier transform

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
TR01 Transfer of patent right

Effective date of registration: 20210617

Address after: 650300 room 211, No.8 Tai'an Road, taipingxincheng Street office, Anning City, Kunming City, Yunnan Province

Patentee after: Yunnan poly Tiantong underwater equipment Technology Co.,Ltd.

Address before: Room 1703, building 1, Linghui Business Plaza, 278 Suzhou Avenue East, Suzhou Industrial Park, Suzhou area, China (Jiangsu) pilot Free Trade Zone, Suzhou 215002, Jiangsu Province

Patentee before: Suzhou high Airlines intellectual property rights Operation Co.,Ltd.

Effective date of registration: 20210617

Address after: Room 1703, building 1, Linghui Business Plaza, 278 Suzhou Avenue East, Suzhou Industrial Park, Suzhou area, China (Jiangsu) pilot Free Trade Zone, Suzhou 215002, Jiangsu Province

Patentee after: Suzhou high Airlines intellectual property rights Operation Co.,Ltd.

Address before: No.2, Mengxi Road, Jingkou District, Zhenjiang City, Jiangsu Province, 212008

Patentee before: JIANGSU University OF SCIENCE AND TECHNOLOGY

TR01 Transfer of patent right