Systems Engineering and Electronics ›› 2018, Vol. 40 ›› Issue (5): 968-975.doi: 10.3969/j.issn.1001-506X.2018.05.02

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Direct trajectory determination algorithm based on evolutionary particle filter

LU Zhiyu, BA Bin, REN Yanqing, WANG Daming   

  1. College of Information System Engineering, Information Engineering University, Zhengzhou 450001, China
  • Online:2018-04-28 Published:2018-04-24

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Abstract:

The traditional tracking algorithms measure the positional parameters such as the time of arrival (TOA) and Doppler shift. In the first step, and in the second step use these parameters to estimate the trajectory of the transmitter. Because of the position information loss and error accumulation, the two-step method is falling to get the best tracking performance. In order to solve this problem, a direct trajectory determination algorithm based on the evolutionary particle filter is proposed, which proves to be more precise for weak signals than the conventional approach. The algorithm exploits the TOA and Doppler shift contained in the sampled signals to establish a direct tracking model based on continuous time information, and then uses the evolutionary particle filter to solve the problem of high computation load. The last but important result is a derivation of closed-form expressions of the Cramer-Rao lower bound (CRLB). The simulation results show that,the algorithm proposed in this paper outperforms the traditional algorithms with more accurate results and higher computational efficiency. Especially in the low signal-to-noise ratio, it is more close to the CRLB.

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