Micro-Doppler Analysis and Separation Based on Complex Local Mean Decomposition for Aircraft With Fast-Rotating Parts in ISAR Imaging

In traditional inverse synthetic aperture radar (ISAR) imaging of aircraft, rigid-body motion is usually assumed, and a focused ISAR image can be obtained using the classical range-Doppler algorithm after the translational motion compensation. However, in real-world situations, nonrigid-bodies such as the fast-rotating blades, propellers or turbofans are often present in aircraft. The ISAR image of the main body will be shadowed by the micro-Doppler (m-D) induced by the rotating parts of the target, whereas the m-D parameter estimation of the rotating parts also becomes more difficult because of the interference from the main body returns. To solve this problem, the Doppler frequency difference between the main body and the rotating parts of the aircraft is analyzed and the complex local mean decomposition (CLMD) is applied to separate the m-D signature in the ISAR imaging. The CLMD method can separate the oscillation mode embedded in signals accurately and decompose the complex modulation nonstationary signals adaptively into some stable monocomponents. After the separation, better geometrical features of the main body and better m-D features of the rotating parts can be obtained by processing each independently. The results from the simulated and measured data are given to verify the validity of the algorithm proposed in this paper.