CPHD-DOA Tracking of Multiple Extended Sonar Targets in Impulsive Environments

被引:83
作者
Saucan, Augustin-Alexandru [1 ]
Chonavel, Thierry [1 ]
Sintes, Christophe [1 ]
Le Caillec, Jean-Marc [1 ]
机构
[1] Inst Mines Telecom Telecom Bretagne, CNRS, UMR 6285, LabSTICC Lab, F-29238 Brest, France
关键词
CPHD filter; DOA tracking; extended target; multivariate Laplace distribution; track before detect; RANDOM FINITE SETS; PARAMETRIC LOCALIZATION; PHD; APPROXIMATION; SIMULATION; NUMBER;
D O I
10.1109/TSP.2015.2504349
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, we propose a novel phased-array track before detect (TBD) filter for tracking multiple distributed (extended) targets from impulsive observations. Since the targets are angularly spread, we track the centroid Direction Of Arrival (DOA) of the target-generated (or backscattered) signal. The main challenge stems from the random target signals that, conditional to their respective states, constitute non-deterministic contributions to the system observation. The novelty of our approach is twofold. First, we develop a Cardinalized Probability Hypothesis Density (CPHD) filter for tracking multiple targets with non-deterministic contributions, more specifically, Spherically Invariant Random Vector (SIRV) processes. This is achieved by analytically integrating the SIRV and angularly distributed target signals in the update step. Thus, ensuring a more efficient implementation than existing solutions, that generally consider augmenting the target state with the target signal. Secondly, we provide an improved auxiliary particle CPHD filter and clustering methodology. The auxiliary step is carried out for persistent particles, while for newly birthed particles an adaptive importance distribution is given. This is in contrast with existing solutions that only consider the auxiliary step for birthed particles. Simulated data results showcase the improved performance of the proposed filter. Results on real sonar phased-array data are presented for underwater 3D image reconstruction applications.
引用
收藏
页码:1147 / 1160
页数:14
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