Slant-range velocity estimation based on Small-FM-Rate Chirp

This paper deals with the estimation of the slant-range velocity of a moving target with airborne SAR data. For the signature of a moving target, performing the Beat Frequency (BF) algorithm in the slow time and range frequency domain can generate a Small-FM-Rate Chirp (SFRC), which has some features of a single-frequency signal. The Fourier transform of such SFRC quite approximates a sinc function, and the maximum-value point of such Fourier transform is proportional to the slant-range velocity. Based on these principles, a methodology known as Beat Frequency Coherent Accumulation (BFCA) algorithm is developed to estimate the slant-range velocity. The prominent advantage of the BFCA algorithm is that the unambiguous velocity can be very large. Besides, the proposed methodology can deal with large range cell migration (RCM) and can work with a low signal-to-noise ratio (SNR) scene, requiring a small amount of computation but yields a high accuracy especially for the fast-moving targets. The effectiveness and efficiency of the proposed methodology are validated with both simulated and real data.