High resolution range profile reconstruction for rotating targets based on random stepped frequency signal

To extract the micro-motion parameters of the rotating targets, SFS (Stepped Frequency Signal) is usually adopted to obtain the HRRP (High Resolution Range Profile). To reduce the sub-frequency counts SFS needs to synthesize the wideband, RSFS (Random Stepped Frequency Signal) is raised. By randomly transmitting the sub-frequencies of SFS, the frequency counts are obviously reduced. Then HRRP reconstruction algorithms based on compressed sensing theory are proposed for the received sparse echo. Both math simulations and field experiments are conducted to prove the effectiveness of the proposed algorithm. The experiment results indicate that when the selected sub-frequency count of the RSFS is no less than some lower bounds, the recovered HRRP is qualified for the micro-motion parameter extraction of the rotating targets.