一种新的窄带雷达高速机动多目标检测算法

Novel detection algorithm for high-speed maneuvering multi-target with narrowband radar

笔者提出一种高速匀加速机动多目标检测算法.首先,通过速度搜索和二阶keystone变换校正距离徙动.距离徙动校正后,目标所在的距离单元方位向回波可建模为线性调频信号.其次,对方位向回波依次进行Lvs变换,目标能量在中心频率-调频率域积累出峰值,根据峰值在调频率维的位置可得到一个加速度的估计值.最后,根据加速度估计值构造补偿函数对多普勒频率徙动进行补偿,并通过快速傅里叶变换实现相参积累,然后再进行目标检测与径向速度估计.该算法与Radon-分数阶傅里叶变换算法相比,具有计算量小、抗噪声性能强的优点.仿真与实测数据处理结果验证了该算法的有效性.

A novel detection method for the high-speed maneuvering multi-target with a constant acceleration is proposed. Firstly, velocity searching and Second-order Keystone Transform （SKT） are jointly applied to correct the range migration （RM）. After the RM correction, the azimuth echoes can be considered as a Linear Frequency Modulation （LFM） signal. Secondly, Lv＇s Transform （LVT） is performed on the azimuth echoes, target energy will be accumulated into a sole peak in the Centroid Frequency （CF）-Chirp Rate （CR） domain, and an estimated acceleration can be obtained in terms of the peak＇s location in the CR-axis. Finally, according to the estimated acceleration, a compensation function is constructed to compensate the Doppler Frequency Migration （DFM）, after that, the FFT is applied to accomplish coherent integration, and then target detection is carried out, meanwhile, the target＇s radial velocity can be estimated, Compared with the Radon-Fractional Fourier Transform （RFRFT）, the proposed algorithm possesses the advantages of lower computational complexity and better anti-noise performance. The results o[ simulation and real data demonstrate the validity of the proposed algorithm.