Journal of Jilin University(Engineering and Technology Edition) ›› 2018, Vol. 48 ›› Issue (6): 1938-1944.doi: 10.13229/j.cnki.jdxbgxb20170585

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DOA tracking algorithm using dynamic compressed sensing

SHAN Ze-biao1,2(),LIU Xiao-song1,3(),SHI Hong-wei1,WANG Chun-yang1,SHI Yao-wu2   

  1. 1. School of Electronic and Information Engineering, Changchun University of Science and Technology, Changchun 130022,China
    2. College of Communication Engineering, Jilin University, Changchun 130022, China
    3. Northwest Weapon Industry Research School, Xi'an Technologyical University,Xi'an 710021,China
  • Received:2017-06-06 Online:2018-11-20 Published:2018-12-11

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Abstract:

In order to solve the problem that the performance of Direction of Arrival (DOA) tracking of dynamic target algorithm deteriorates under single snapshot, a DOA tracking method using dynamic compressed sensing is proposed in this article. Firstly, by extracting priori information about sparsity from last signal vector, we estimate the probability of the elements being non-zero and build a sparsity probability model of dynamic DOA in the present signal vector. Secondly, we get the locations of nonzero elements of present signal vector and achieve real-time DOA tracking of dynamic targets by applying this sparsity probability model to the reconstruction of sparse signals and minimizing a weighted norm. This method can obtain real-time DOA tracking of dynamic targets in a single snapshot condition and has better tracking performance than particle filter under the same conditions. Finally, the effectiveness of proposed algorithm is verified by numerical simulation results.

Key words: information processing technology, direction of arrival(DOA) tracking, dynamic compressed sensing, sparsity probability model, weighted l1 minimization

CLC Number: 

  • TN911

Fig.1

Variation of nonzero element Sj with sampling time"

Fig.2

Probability distribution of the position of nonzero Sjt-1 element at sampling time t"

Fig.3

Probability vector pt calculated from S(t-1)(σ=2)"

Fig.4

RMSEs of DOA tracking with different σ"

Fig.5

Tracking errors comparison of different algorithms"

Fig.6

RMSEs of DOA tracking of three algorithms versus SNRs"

Fig.7

RMSEs of DOA tracking of three algorithms versus numbers of antenna"

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