## 1 Introduction  
Radar imaging is the reconstruction of a radar target from recorded data. The traditional imaging method is to perform spectrum analysis using a two-dimensional Fourier transform. The Fourier transform can show which frequency components are contained in the signal, but cannot show how the frequency changes with time. The literature [1; 2] proposes the use of time-frequency analysis for radar moving target imaging. Each time-frequency tool has different effects on radar imaging. Mechanical vibration or rotation of a target or structures on the target may induce additional frequency modulations on the radar echo signal which generate sidebands about the target's Doppler frequency, called the micro-Doppler effect. It is mainly caused by the rotation of propellers or rotor wings on a plane. Up until now, various research has been done on the m-D effect. But most of it has been limited to the microwave approach only. The time-frequency analysis method separates target from micro-Doppler information [3; 4; 5]. Time-frequency analysis can be used in feature extraction or parameter estimation of m-D components [6; 7]. The Viterbi algorithm divides the micro-Doppler components [8; 9]. The windowed time-frequency analysis and the Radon transform are used to isolate or suppress the micro-Doppler element [10]. The S-transform (ST), a well-known time-frequency analysis tool, has been deeply researched since it was proposed by Stockwell in 1996 [11] and has been used in many fields such as radar signal processing [12; 13] and disposal of medical signals [14; 15]. In some cases, the S-transform is also considered a special case of wavelet transform, while the usual wavelet transform does not have an inverse transform. The S-transform has three major advantages. First, the S-transform is a linear transform with no cross-term interference. Second, the S-transform has a unique inverse transform. Finally, the S-transform has multiple resolutions, better time resolution at high frequency and better frequency resolution at low frequency. In view of third merit, S-transform is especially suitable for analyzing radar echo signals for imaging. Its high frequency domain resolution in the low frequency region can achieve accurate imaging of the target rigid body component while the time domain resolution advantage of the high frequency region can effectively provide the target micro-Doppler information. In recent years, the micro-Doppler effect on laser radar has gradually attracted attention in the field of radar. Inverse synthetic aperture imaging laser (ISAIL) [16] is such a coherent laser radar, the micron-size working wavelength makes a sensitive detection of the m-D effect of target. The impact of the micro-Doppler effect on ISAIL imaging is mainly reflected in two aspects. First, the micro-Doppler effect will make the Doppler broadening of the corresponding distance unit echo and the resulting ISAIL image will be affected by the micro-Doppler component. Strip-shaped interference makes it difficult to understand the target image and extract the target features. Second, the micro-Doppler component in the echo contains a wealth of moving component motion feature information, which can provide more accurate target dynamic features. This provides a new way to analyze target characteristics. Therefore, how to separate the micro-Doppler component from the target echo and ensure the integrity of the two signals to meet the requirements of ISAIL imaging and target moving component motion feature analysis has become an important research topic. In order to solve the above problems, this paper proposes an algorithm based on Random Sample Consensus [17; 18; 19] (RANSAC) to separate rigid body and micro-Doppler information. Clear radar imaging is obtained by using S-transformation.