Passive Sonar Multiple Target Tracking with Different Resampling Algorithms

被引：0

作者：

Ozer, Erhan ^{[1
]}

Akar, Ali Onur ^{[1
]}

Hocaoglu, Ali Koksal ^{[1
]}

机构：

[1] Gebze Tekn Univ, Elekt Muhendisligi Bolumu, Kocaeli, Turkey

来源：

2018 26TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2018年

关键词：

Bayesian; Nonlinear systems; Systems without normal distribution; Tracking; State space estimation; Sequential Monte Carlo estimation; Multiple target; Target Motion Analysis; bearing only tracking; FILTER;

D O I：

暂无

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 addition to many new application areas that have entered our lives, the need for identification of nonlinear systems has been born. Especially in the estimation of dynamic systems which has Non-Gaussian Measurement Noise; Kalman, grid-based etc. algorithms do not provide an optimal solution. Particle filter can estimate dynamics of nonlinear systems more accurately and realistically without assuming measurement noise distribution. In this study, particle filter was used in the application of multiple target tracking in passive sonar with different resampling methods. In simulations, the performance differences of the Minimum Variance (MSV) method were analyzed based on other classical resampling methods for the problem of passive sonar multi-target tracking.

引用

页数：4

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