Abstract: The disclosed are a signal processing method, a signal processing device, a radar, a medium, a program product and a terminal. The method is applied to the radar, the radar includes M transmit channels, and the method includes: transmitting, during a first transmit cycle, a first detection signal through the M transmit channels; transmitting, during a second transmit cycle, a second detection signal through ml transmit channels in the M transmit channels, where m1<M, M is an integer greater than 0; and processing a first echo signal and a second echo signal to determine a correspondence between the first echo signal and the M transmit channels; where the first echo signal and the second echo signal are signals generated after the first detection signal and the second detection signal being reflected by a target, respectively. It is advantageous to better meet the radar measurement needs.

Abstract: The present disclosures discloses a method of target feature extraction based on millimeter-wave radar echo, which mainly solves the problems that techniques in the prior art cannot fully utilize raw radar echo information to obtain more separable features and cannot accurately distinguish targets with similar physical shapes and motion states. The method is implemented as follows: acquiring measured data of targets, generating an original RD map, and removing ground clutter of the map; sequentially performing target detection, clustering and centroid condensation on the RD map after the ground clutter removal; acquiring a continuous multi-frame RD maps and carrying out the target tracking; according to the tracking trajectory, selecting candidate areas and extracting features based on a single piece of RD map and features based on two successive RD maps, respectively.

Abstract: The present disclosures discloses a method of target feature extraction based on millimeter-wave radar echo, which mainly solves the problems that techniques in the prior art cannot fully utilize raw radar echo information to obtain more separable features and cannot accurately distinguish targets with similar physical shapes and motion states. The method is implemented as follows: acquiring measured data of targets, generating an original RD map, and removing ground clutter of the map; sequentially performing target detection, clustering and centroid condensation on the RD map after the ground clutter removal; acquiring a continuous multi-frame RD maps and carrying out the target tracking; according to the tracking trajectory, selecting candidate areas and extracting features based on a single piece of RD map and features based on two successive RD maps, respectively.