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A Fixed Single Station Location Tracking Method Based on Spatial and Frequency Domain Information

Published: 25 February 2022 Publication History

Abstract

In order to solve the problem of calculate the radiation source target position in the passive localization of a moving target by a fixed single station, a real-time localization tracking method based on spatial and frequency domain information is proposed. Firstly, the time of arrival difference(TOA) is added into the localization algorithm to improve the measurement accuracy of Doppler frequency change rate. Then, the extended Kalman filter (EKF) and immune algorithm (IA) are introduced to optimize the coupling problem of particle scarcity and weight degradation in the particle filter algorithm. Finally, by using the optimized filter algorithm to process the localization results, the measurement error and acceleration disturbance in the localization algorithm can be reduced, and more accurate target track can be obtained. The simulation results show that the relative range error (RRE) of the improved localization algorithm is reduced by 2.48% compared with the traditional localization algorithm, and the average RRE of the particle filter algorithm optimized by EKF and IA is 2.75% lower than the traditional particle filter algorithm. The improved algorithm shows better robustness and can locate and track the moving target in the concealed condition.

References

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H. Zhong, H. Ruan and B. Sun, "An Algorithm of the DPFRC real-time Location for The Moving Emmiter by a Moving Singal Observer," 2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference (ITAIC),2019, pp. 168-172.
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TIAN Minghui, MA Min, ZHANG Wenyi. Target localization and tracking based on azimuth measurement and velocity estimation J. Journal of Terahertz Science and Electronic Information Technology,2019,17(01):69-73.
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YU Tao. Analytic method of bearing-only target motion parameter for fixed single-station J. Chinese Journal of Radio Science, 2014,29(04): 634-638,652.
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J. Brown, "FM Airborne Passive Radar". PhD thesis. University College London, April 2013.
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SUN Peng, XIONG Wei. Analysis of an Improved Fixed Single Station Passive Location Model J. Fire Control & Command Control, 2016,41(06):82-86.
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GUO Fucheng. Tracking algorithm of fixed mono-station passive radar using TOA and DOA J. Journal of Terahertz Science and Electronic Information Technology,2015,13(06):908-912.
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        AIPR '21: Proceedings of the 2021 4th International Conference on Artificial Intelligence and Pattern Recognition
        September 2021
        715 pages
        ISBN:9781450384087
        DOI:10.1145/3488933
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        Published: 25 February 2022

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        Author Tags

        1. Extended Kalman filter
        2. Particle filter
        3. Passive localization
        4. Real-time tracking
        5. Time difference of arrival

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