一种新的高速多目标参数检测算法

A Novel Parametric Detection Method for High-Speed Multi-Target

  • 摘要: 该文提出一种新的高速、多目标窄带雷达目标检测和参数估计算法。首先采用基于循环平稳的联合Keystone变换与模糊数搜索方法完成目标运动参数粗估计,然后在粗估计基础上采用联合频域距离徙动补偿处理与分数阶傅里叶变换方法完成目标检测及参数估计。该算法适用于多目标及存在距离徙动、多普勒扩散和多普勒模糊的情况,其保持了循环平稳计算复杂度低的优点,且克服了已有循环平稳算法在工程应用中估计精度低和运动参数估计范围受限的缺陷。计算机仿真和实测数据验证了算法的有效性。

     

    Abstract: A novel algorithm for high-speed multi-target detection and parameters estimation with narrowband radar is proposed in this paper. Firstly, base on cyclostationarity, moving parameters are roughly estimated with the joint Keystone transform and ambiguity searching. And then, according to the coarse estimation, the joint compensating range migration in frequency domain and fractional Fourier transform are utilized to conduct the targets detection and parameters estimation. In the case of multi-target, range migration, Doppler spread and Doppler ambiguity, this algorithm is suitable, and retains the merit of low computational complexity of cyclostationarity. Compared with existing cyclostationarity based algorithms, the weaknesses of low estimation precision and limited range of moving parameters are conquered in engineering applications. The validity of the proposed algorithm is demonstrated by computer simulation and raw radar data results.

     

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