In conventional inverse synthetic aperture radar (ISAR) imaging of complex moving aircrafts, a micro-Doppler effect is generated because of the high-speed rotating parts such as propellers. The rotational parts introduce a sinusoidal frequency-modulated (SFM) signal in the radar echoes, which can significantly affect the quality of the ISAR imaging. To solve this problem, the Doppler frequency forms for the rigid body and rotating parts of an aircraft are analyzed, and a method based on the discrete sinusoidal frequency-modulated transform (DSFMT) is proposed. The SFM signal can be transformed into the DSFMT domain, and the parameters can be estimated by the global maximum. The rigid body is separated after removing the SFM signals using successive elimination technology. This method is not only applicable to targets in uniform motion but also to those in accelerating motion. The results of simulations and a measured data test are given to verify the effectiveness of the proposed method.
In recent years, the geosynchronous satellite-based passive inverse synthetic aperture radar (ISAR) has been widely employed for target detection and automatic target recognition. However, the great distance between the satellite and the receiver causes low signal-to-noise ratio (SNR) of the target signal, which makes the system unable to obtain a well-focused image of the target. To obtain a well-focused ISAR image within a limited coherent processing interval, a method for improving the SNR is required. We propose a two-step noise suppression method to enhance the SNR by eliminating the noise components contained in the received data. The target windowing method is utilized first to reject the noise and clutter interference by windowing the target data from the range-Doppler map. Then, a denoising method is employed to further remove the noise components from the selected target data by threshold techniques. By using the two-step noise suppression, the SNR of the target signal is increased, and consequently a quality-improved ISAR image can be obtained. Simulation results validate the effectiveness of the proposed noise suppression method.
Inverse Synthetic Aperture Radar system provides high-resolution images of the observed targets with non-cooperative movement. The received signal can take the form of the multicomponent cubic phase signal, and the ISAR image can be generated by the parameters estimation of it. In the real situation, the amplitude of the received signal is varying during the time of observation because of the scatterers Migration Through Resolution Cells (MTRC) and this phenomenon cannot be neglected to get a well-focused ISAR image. In this study, we use the Modified Cubic Function (MCPF) to estimate the phase parameters of the echo and we propose a Special Narrow Spectrum Filter (SNSF) technique to estimate the time varying amplitude. The ISAR image can be enhanced based on the proposed technique ((MCPF plus SNSF)) compared with the previous version (MCPF plus constant amplitude). The experimental work proves the effectiveness of the proposed method.
A method for estimating the parameters of the sinusoidal frequency modulation (SFM) signal is presented in this paper. Based on the modified discrete sinusoid frequency modulation transform (DSFMT), the SFM signal can be transformed into the DSFMT domain where it is energy-concentrated and then the parameters can be estimated by the global maximum. To search for the location of the global maximum with less computational load, particle swarm optimization is used in this paper. Then the algorithm is used in the synthetic aperture radar imaging with high frequency vibration of the platform, and the focus performance can be improved significantly. Simulation results demonstrate the effectiveness of the method proposed in this paper.