The CAF-DFRFT-KT Algorithm for High-Speed Target Detection in Passive Radar

The cross-ambiguity algorithm has been extensively used to detect targets in passive radar. However, this algorithm is affected by range migration and Doppler frequency migration when detecting high-speed and accelerating targets. In this paper, an effective algorithm of compensating the two migrations in passive radar is presented. The presented algorithm combines the fractional Fourier transform and the keystone transform with the cross-ambiguity function algorithm. Based on the cross-ambiguity function, the fractional cross-ambiguity function algorithm is realized by the two-step FFTs, and then the keystone transform is inserted into the two-step FFTs. The presented algorithm can eliminate the effects of range migration and Doppler frequency migration. Simulation results are conducted to demonstrate the validity of the presented algorithm.