Multi‐aspect micro‐Doppler signatures for attitude‐independent L / N quotient estimation and its application to helicopter classification

Abstract

Micro-Doppler signals returned from the main rotor of a helicopter can be used for feature extraction and helicopter classification. An intrinsic feature of a helicopter that may be extracted from the micro-Doppler signatures is the L/N quotient, where N denotes the number of rotor blades and L is the blade length. However, in monostatic radar, the L/N quotient cannot be accurately estimated due to the unknown attitude angles of non-cooperative helicopters. To solve this problem, an attitude-independent L/N quotient estimation method based on multi-aspect micro-Doppler signatures is proposed in this study. The helicopter is observed from different aspect angles, and the multi-aspect micro-Doppler signatures are jointly processed to solve the attitude angles of the helicopter and estimate the L/N quotient unambiguously. Experiments with both simulated and real data demonstrate that, the proposed method is robust with respect to the attitude of the helicopter and, therefore, significantly improves the accuracy of L/N quotient estimation compared with only using the signature observed from single-aspect angle. This implies that the proposed method has the potential to increase the success rate of helicopter classification.