Micro-Doppler Curve Extraction Based on Reassociation Viterbi Algorithm
Jing Wu, Xiaofeng Ai, Yuqing Zheng, Zhiming Xu, Feng Zhao
Abstract
The accurate extraction of micro-Doppler (m-D) curves is crucial for target recognition for space targets. However, the strong overlap of m-D curves and the noise disturbance of multi-component non-stationary signals in the time-frequency domain make it a great challenge to separate these curves using conventional algorithms. To address this problem, a curve extraction algorithm for multicomponent m-D signals based on the reassociation Viterbi algorithm (RVA) is proposed in this paper. First, the Viterbi algorithm is combined with an adaptive curve removal method for curve detection in a multicomponent m-D signal. Then, a two-step association method based on distance and velocity is presented to achieve correct curve separation. In addition, a variable threshold algorithm is introduced to extract both strong and weak components. Finally, the improved validity and robustness of the proposed algorithm have been verified by experiments compared to conventional methods.