DOA Tracking Algorithm Based on AVS Pseudo-Smoothing for Coherent Acoustic Targets
A direction-of-arrival (DOA) tracking algorithm based on AVS pseudo-smoothing, referred to as the FOC-M<inline-formula><tex-math notation="LaTeX">\delta</tex-math></inline-formula>-GLMBF algorithm, is proposed to track coherent acoustic targets. This algorithm adapt...
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| Published in: | IEEE transactions on aerospace and electronic systems Vol. 59; no. 6; pp. 1 - 19 |
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01.12.2023
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| ISSN: | 0018-9251, 1557-9603 |
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| Abstract | A direction-of-arrival (DOA) tracking algorithm based on AVS pseudo-smoothing, referred to as the FOC-M<inline-formula><tex-math notation="LaTeX">\delta</tex-math></inline-formula>-GLMBF algorithm, is proposed to track coherent acoustic targets. This algorithm adapts the marginalized <inline-formula><tex-math notation="LaTeX">\delta</tex-math></inline-formula>-generalized labeled multi-Bernoulli (M<inline-formula><tex-math notation="LaTeX">\delta</tex-math></inline-formula>-GLMB) fast filtering algorithm with the fourth-order cumulants (FOC) pseudo-smoothing. It introduces higher-order cumulants capable of suppressing Gaussian noise, and constructs the cumulant matrices and the likelihood function that can be used for AVS pseudo-smoothing. The processing enhances the signal-to-noise ratio (SNR) by suppressing measurement noise, and can accomplish decoherence when there are coherent targets. Based on the labeled random finite set (RFS), it additionally introduces the index label to distinguish different motion models as hidden states, and achieves better tracking performance through the weighted mixture of multiple models. By using the AVS hybrid signal as the measurement, the algorithm avoids measurement-to-track association maps in the filtering process, to effectively support the tracking problem when targets are close to each other or have intersecting trajectories. In addition, as a joint prediction-and-update strategy, the algorithm performs the hypothesis truncation by the K-shortest path method only once, thereby further compensating for the burden of cumulant calculation. Simulations and field experiments verify the superiority of the proposed tracking algorithm for coherent targets under low SNR. |
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| AbstractList | A direction-of-arrival (DOA) tracking algorithm based on acoustic vector sensor (AVS) pseudosmoothing, referred to as the FOC-M$\delta$-GLMBF algorithm, is proposed to track coherent acoustic targets. This algorithm adapts the marginalized $\delta$-generalized labeled multi-Bernoulli (M$\delta$-GLMB) fast filtering algorithm with the fourth-order cumulants pseudosmoothing. It introduces higher-order cumulants capable of suppressing Gaussian noise, and constructs the cumulant matrices and the likelihood function that can be used for AVS pseudosmoothing. The processing enhances the signal-to-noise ratio (SNR) by suppressing measurement noise, and can accomplish decoherence when there are coherent targets. Based on the labeled random finite set (RFS), it additionally introduces the index label to distinguish different motion models as hidden states, and achieves better tracking performance through the weighted mixture of multiple models. By using the AVS hybrid signal as the measurement, the algorithm avoids measurement-to-track association maps in the filtering process, to effectively support the tracking problem when targets are close to each other or have intersecting trajectories. In addition, as a joint prediction-and-update strategy, the algorithm performs the hypothesis truncation by the K-shortest path method only once, thereby further compensating for the burden of cumulant calculation. Simulations and field experiments verify the superiority of the proposed tracking algorithm for coherent targets under low SNR. A direction-of-arrival (DOA) tracking algorithm based on AVS pseudo-smoothing, referred to as the FOC-M<inline-formula><tex-math notation="LaTeX">\delta</tex-math></inline-formula>-GLMBF algorithm, is proposed to track coherent acoustic targets. This algorithm adapts the marginalized <inline-formula><tex-math notation="LaTeX">\delta</tex-math></inline-formula>-generalized labeled multi-Bernoulli (M<inline-formula><tex-math notation="LaTeX">\delta</tex-math></inline-formula>-GLMB) fast filtering algorithm with the fourth-order cumulants (FOC) pseudo-smoothing. It introduces higher-order cumulants capable of suppressing Gaussian noise, and constructs the cumulant matrices and the likelihood function that can be used for AVS pseudo-smoothing. The processing enhances the signal-to-noise ratio (SNR) by suppressing measurement noise, and can accomplish decoherence when there are coherent targets. Based on the labeled random finite set (RFS), it additionally introduces the index label to distinguish different motion models as hidden states, and achieves better tracking performance through the weighted mixture of multiple models. By using the AVS hybrid signal as the measurement, the algorithm avoids measurement-to-track association maps in the filtering process, to effectively support the tracking problem when targets are close to each other or have intersecting trajectories. In addition, as a joint prediction-and-update strategy, the algorithm performs the hypothesis truncation by the K-shortest path method only once, thereby further compensating for the burden of cumulant calculation. Simulations and field experiments verify the superiority of the proposed tracking algorithm for coherent targets under low SNR. |
| Author | Yang, Jianhua Chen, Zhifei Zhang, Jun Bao, Ming Hou, Hong |
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| References | ref13 ref57 ref12 ref56 ref15 ref59 ref14 ref53 ref52 ref11 ref10 ref17 ref19 ref18 Chen (ref78) 2015; 47 Thouin (ref54) 2011 ref51 ref50 ref46 ref45 ref48 ref47 ref42 ref41 Yang (ref16) 2019 ref44 ref43 ref49 ref8 ref7 Mahler (ref25) 2007 ref9 ref4 ref3 Choppala (ref58) 2014 ref6 ref5 ref40 ref35 ref79 ref34 ref37 ref36 ref31 ref75 ref30 ref74 Zhong (ref21) 2011 ref33 ref77 ref32 ref76 ref2 ref1 ref38 Hoang (ref39) 2015 ref71 ref70 ref73 ref72 ref24 ref68 ref23 ref67 ref26 ref69 ref20 Nannuru (ref55) 2013 ref64 ref63 ref22 ref66 ref65 ref28 ref27 ref29 ref60 ref62 ref61 |
| References_xml | – ident: ref79 doi: 10.2514/3.8233 – ident: ref27 doi: 10.1109/TSP.2006.881190 – ident: ref11 doi: 10.1109/TSP.2020.3021237 – ident: ref38 doi: 10.1109/TSP.2016.2641392 – ident: ref13 doi: 10.1109/79.221324 – ident: ref6 doi: 10.1109/48.650832 – ident: ref1 doi: 10.1109/78.317869 – ident: ref67 doi: 10.1109/29.17496 – ident: ref50 doi: 10.1155/2013/727430 – ident: ref64 doi: 10.1109/OCEANS-Genova.2015.7271632 – ident: ref75 doi: 10.1016/j.sigpro.2008.04.010 – ident: ref23 doi: 10.1109/TAC.1979.1102177 – start-page: 999 volume-title: Proc. Int. Conf. Inf. Fusion year: 2015 ident: ref39 article-title: A fast implementation of the generalized labeled multi-Bernoulli filter with joint prediction and update – ident: ref59 doi: 10.3390/s19184031 – ident: ref69 doi: 10.1109/lawp.2005.860194 – ident: ref17 doi: 10.1109/78.978374 – start-page: 245 volume-title: Proc. Eur. Signal Proces. Conf. year: 2011 ident: ref21 article-title: Particle filtering for 2-D direction of arrival tracking using an acoustic vector sensor – start-page: 2247 volume-title: Proc. IEEE Adv. Inf. Technol. Electron. Autom. Control Conf. year: 2019 ident: ref16 article-title: An indirect location method for indoor target tracking based on single acoustic vector sensor – ident: ref74 doi: 10.1109/joe.2009.2036554 – ident: ref24 doi: 10.1109/TSP.2007.908968 – ident: ref49 doi: 10.1109/TAES.2013.6621845 – ident: ref32 doi: 10.1109/TAES.2012.6178069 – ident: ref9 doi: 10.1109/TSP.2006.870630 – ident: ref41 doi: 10.1109/IVS.2017.7995809 – ident: ref7 doi: 10.1109/48.838989 – ident: ref73 doi: 10.1049/iet-rsn:20050140 – ident: ref76 doi: 10.1016/j.dsp.2008.01.002 – ident: ref34 doi: 10.1109/TSP.2014.2364014 – ident: ref19 doi: 10.1109/ICME.2011.6011965 – ident: ref4 doi: 10.1109/78.709509 – ident: ref31 doi: 10.1109/LSP.2014.2310137 – start-page: 1632 volume-title: Proc. Int. Conf. Inf. Fusion Istanbul Turkey year: 2013 ident: ref55 article-title: Multi-Bernoulli filter for superpositional sensors – ident: ref44 doi: 10.1109/9.1299 – ident: ref8 doi: 10.1109/78.806070 – ident: ref5 doi: 10.1109/78.960397 – ident: ref51 doi: 10.1109/CISP-BMEI53629.2021.9624459 – ident: ref43 doi: 10.1109/7.640267 – ident: ref12 doi: 10.1109/5.75086 – ident: ref62 doi: 10.1109/TSP.2012.2199987 – ident: ref3 doi: 10.1121/1.3676699 – ident: ref52 doi: 10.1016/j.sigpro.2019.05.028 – ident: ref57 doi: 10.1109/LCOMM.2021.3099569 – ident: ref72 doi: 10.1109/JSEN.2007.900963 – ident: ref60 doi: 10.1109/ICCAIS46528.2019.9074571 – ident: ref71 doi: 10.1109/JSEN.2014.2327633 – ident: ref14 doi: 10.1109/78.382404 – ident: ref30 doi: 10.1109/TSP.2013.2257765 – ident: ref18 doi: 10.1109/78.978377 – ident: ref68 doi: 10.1109/78.506626 – ident: ref46 doi: 10.1109/7.826308 – start-page: 1 volume-title: Proc. Int. Conf. Inf. Fusion year: 2014 ident: ref58 article-title: Adapting the multi-Bernoulli filter to phased array observations using MUSIC as pseudo-likelihood – ident: ref65 doi: 10.1109/TVT.2021.3093063 – ident: ref45 doi: 10.1109/TAES.2004.1292168 – ident: ref48 doi: 10.1016/j.sigpro.2011.11.032 – volume-title: Statistical Multisource-Multitarget Information Fusion year: 2007 ident: ref25 – ident: ref2 doi: 10.1109/78.482014 – ident: ref40 doi: 10.1109/TAES.2019.2941104 – ident: ref10 doi: 10.1109/JOE.2019.2934211 – ident: ref36 doi: 10.1109/tsp.2014.2323064 – ident: ref29 doi: 10.1109/tsp.2008.2007924 – ident: ref61 doi: 10.1109/ACCESS.2020.3048952 – ident: ref28 doi: 10.1109/taes.2005.1561884 – ident: ref22 doi: 10.1109/JOE.1983.1145560 – ident: ref35 doi: 10.1109/TSP.2013.2259822 – start-page: 1 volume-title: Proc. Int. Conf. Inf. Fusion year: 2011 ident: ref54 article-title: Multi-target tracking for measurement models with additive contributions – volume: 47 start-page: 377 issue: 3 year: 2015 ident: ref78 article-title: DOA tracking algorithm for acoustic vector-sensor array via kalman filter and OPASTD publication-title: Trans. Nanjing Univ. Aeronaut. Astronaut. – ident: ref15 doi: 10.1109/OCEANSE.2017.8084844 – ident: ref33 doi: 10.1109/JPROC.2018.2789427 – ident: ref56 doi: 10.1109/TSP.2017.2768025 – ident: ref66 doi: 10.1109/TASSP.1985.1164649 – ident: ref47 doi: 10.1109/TAES.2009.5259174 – ident: ref70 doi: 10.1109/TSP.2010.2077634 – ident: ref37 doi: 10.1287/opre.16.3.682 – ident: ref63 doi: 10.1109/ICASSP.2012.6288458 – ident: ref26 doi: 10.1109/TAES.2003.1261119 – ident: ref77 doi: 10.1016/j.sigpro.2009.03.008 – ident: ref42 doi: 10.1109/LSP.2016.2557078 – ident: ref53 doi: 10.1109/TSP.2015.2504349 – ident: ref20 doi: 10.1109/JSEN.2011.2168204 |
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| SubjectTerms | Acoustic measurements Acoustic vector sensor Acoustics Algorithms Coherence Covariance matrices Direction of arrival Direction-of-arrival estimation Estimation Filtering algorithms Filtration generalized labeled multi-bernoulli higher-order cumulants Noise measurement pseudo-smoothing Random noise Shortest-path problems Signal to noise ratio Target tracking Tracking problem |
| Title | DOA Tracking Algorithm Based on AVS Pseudo-Smoothing for Coherent Acoustic Targets |
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