Abstract—In this paper, a comparison between thetwo algorithms for tracking multiple maneuvering targets in heavy clutter is done. First one is by using Multiple Hypothesis Tracking (MHT) and nonlinear non-Gaussian Kalman filter and the second one is by combining MHT and Real-Time Particle Filter (RTPF). The main difficulty in multiple maneuvering targets tracking is the nonlinearity associated with target states. The multiple target’s motion modes in highly non-linear states are detected by using Multiple Hypothesis Tracking (MHT). In MHT, hypothetical tracks are generated, so the computational burden increases exponentially with number of tracks. So the 1-backscan MHT algorithm is a good alternative because its having good tracking performance and limitation of computation time. The nonlinear non-Gaussian Kalman filter is used to track the target with high maneuver rate and also it gives less probability of missing the target. Tracking by Real-time particle filter (RTPF) uses all sensor information even when the filter update rate is below than that of sensors. In RTPF each posterior is represented as mixture of sample sets, where each mixture component integrates one observation arriving during a filter update. RTPF eliminate the problem of filter divergence due to an insufficient number of independent samples.
Index Terms—Multiple Hypothesis Tracking, nonlinear non-Gaussian Kalman filter, RTPF, tracking of multiple maneuvering Targets.
S.Vasuhi, Lecturer, Department of Electronics Engg , MIT-Anna University, Chrompet, Chennai-600 044, INDIA (e-mail: vasuhi_s@ annauniv.edu ).
V. Vaidehi, Professor, Department of Electronics Engg., MIT-Anna University, Chrompet, Chennai-600 044, INDIA. (e-mail: Vaidehi@annauniv.edu).
Midhunkrishna P, Student-ME (AVIONICS), Department of Electronics Engg., MIT-Anna University, Chrompet, Chennai-600 044, INDIA (e-mail: midhun4krishna@yahoo.co.in).
Cite: S.Vasuhi, V. Vaidehi and Midhunkrishna P.R, "Multiple Maneuvering Targets Tracking Using Kalman and Real-Time Particle Filter A Comparison," International Journal of Engineering and Technology vol. 1, no. 3, pp. 224-230, 2009.
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