Study on Track and Detect Algorithm in Radar Networking Based on GMPHD

doi:10.16182/j.issn1004731x.joss.201611023

Abstract

Abstract: The states and number of WSNR multi-target are tracked accurately by Gaussian mixture probability hypothesis density algorithm (GMPHDA) application. But tracking result is random set of target states, it doesn't correspond one to one with real targets. And the complete algorithm about corresponding has not been proposed. To get target tracks corresponding with real targets, a suite of algorithm about identifying target tracks is proposed, called track identification algorithm, which contains track distinction, continuance, newborn and restoration. The track identification algorithm improves track and detect algorithm in multi-radar networking. Simulation results show that WSNR multi-target is tracked in multi-radar networking, which gets target tracks corresponding one to one with real targets by the proposed identification algorithm.

Key words: track identification, Gaussian mixture probability hypothesis density filter, probability hypothesis density filter, multi-radar networking

CLC Number:

TN953

Zhao Wenbo, Ding Hailong. Study on Track and Detect Algorithm in Radar Networking Based on GMPHD[J]. Journal of System Simulation, 2016, 28(11): 2804-2812.

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