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Particle Filter Tracking Algorithm in LOS/NLOS Hybrid Environment |
Luo Yong-jie; Wan Qun; Yang Wan-lin |
Dept. of E.E., University of Electronic Science and Technology of China, Chengdu 610054, China |
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Abstract Large tracking error has been found in the use of classic extended Kalman filter in LOS/NLOS hybrid environment. This paper presents a modified particle filter algorithm based on the LOS/NLOS binary state information of propagation environment using the numerical method of the Probability Density Function (PDF) about the hybrid noise. Simulation results show that the new scheme integrated the LOS/NLOS environment information and the hybrid noise density can improve the tracking estimation accuracy effectively.
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Received: 19 January 2006
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