基于非均匀FFT的长时间相参积累算法

针对采样引起时域相参积累损失以及相参积累算法运算量较大的问题，该文提出一种在快时间频域实现长时间相参积累的快速算法。该算法在快时间频域利用非均匀快速傅里叶变换(FFT)校正距离走动，完成相位补偿，然后通过快速逆傅里叶变换(IFFT)实现积累。该算法可以避免由采样引起的积累损失且运算量相对较小，理论分析和仿真结果验证了该算法的有效性。

A Long-term Coherent Integration Algorithm Based on Non-uniform Fast Fourier Transform

Sampling may cause some loss for coherent integration in time domain and the computation burdens of the common coherent integration algorithms are usually heavy. To resolve these issues, a fast algorithm realizing long-term coherent integration in fast-time frequency domain is proposed. The algorithm firstly utilizes non-uniform FFT to accomplish range walk correction and phase compensation in fast-time frequency domain, and then fulfills the integration via IFFT. The proposed algorithm can avoid loss entailed by sampling, and needs relatively less computation. The theoretical analysis and simulation results demonstrate the effectiveness of the proposed algorithm.