Frequency modulation continuous wave (FMCW) Lidar inevitably suffers from vibration and nonlinear frequency modulation, which influences the ranging and imaging results. In this paper, we analyze the impact of vibration error coupled with nonlinearity error on ranging for FMCW Lidar, and propose a purely theoretical approach that simultaneously compensates for time-varying vibration and nonlinearity in one-period triangular FMCW (T-FMCW) signals. We first extract the localized characteristics of dechirp signals in time-frequency domain by using a second-order synchro-squeezing transform (second-order SST), and establish an instantaneous ranging model based on second-order SST which can characterize the local distributions of time-varying errors. Second, we estimate the nonlinearity error by using time-frequency information of an auxiliary channel and then preliminarily eliminate the error from the instantaneous measurement range. Finally, we construct a particle filtering (PF) model for T-FMCW using the instantaneous ranging model to compensate for the time-varying vibration error and the residual nonlinearity error, and calculate the range of target by using triangular symmetry relations of T-FMCW. Experimental tests prove that the proposed method can accurately estimate the range of target by compensating for the time-varying vibration and the nonlinearity errors simultaneously in one-period T-FMCW signal.

Airborne multichannel high-resolution radar (HRR)-ground moving target indication (GMTI) is of great significance to wide-area surveillance, traffic monitoring and target recognition. The Aerospace Information Research Institute, Chinese Academy of Sciences, produced an advanced airborne digital array radar with high resolution and conducted an experiment with slow and weak cooperative moving targets in 2021. In this paper, an overall processing framework for target detection, parameter estimation and target tracking using this system is introduced. For HRR detection, the echo energy of targets is spread into multiple range units, so-called range-spread targets; thus, using detectors designed for point-like targets will severely degrade the detection performance, especially for slow and weak targets. To address the adaptive detection of such range-spread targets embedded in Gaussian clutter with an unknown covariance matrix, a novel two-step generalized space-time adaptive processing (GSTAP) algorithm is proposed, which offers an enhanced clutter suppression capability compared with natural competitors. Moreover, a tracking method is implemented in the range-Doppler domain to avoid track loss caused by azimuth relocation error and reject discrete false alarms. Both simulation and experimental results are presented to demonstrate the effectiveness of the proposed method and provide a paradigm for further research.

The post-Doppler adaptive matched filter (PD-AMF) with constant false alarm rate (CFAR) property was developed for adaptive detection of moving targets, which is a standardized version of the post-Doppler space–time adaptive processing (PD-STAP) in practical applications. However, its detection performance is severely constrained by the training data, especially in a dense signal environment. Improper training data and contamination of moving target signals remarkably degrade the performance of disturbance suppression and result in target cancellation by self-whitening. To address these issues, a novel post-Doppler parametric adaptive matched filter (PD-PAMF) detector is proposed in the range-Doppler domain. Specifically, the detector is introduced via the post-Doppler matched filter (PD-MF) and the lower-diagonal-upper (LDU) decomposition of the disturbance covariance matrix, and the disturbance signals of the spatial sequence are modelled as an auto-regressive (AR) process for filtering. The purpose of detecting ground moving targets as well as for estimating their geographical positions and line-of-sight velocities is achieved when the disturbance is suppressed. The PD-PAMF is able to reach higher performances by using only a smaller training data size. More importantly, it is tolerant to moving target signals contained in the training data. The PD-PAMF also has a lower computational complexity. Numerical results are presented to demonstrate the effectiveness of the proposed detector.

High-resolution synthetic aperture radar (SAR) imaging has great application potential in terrain mapping, oceanographic observation, air-to-ground reconnaissance and regional surveillance. Low cost, light weight and multiple modes are important trends in the future development of SAR systems. The Aerospace Information Research Institute, Chinese Academy of Sciences (AIRCAS), developed a state-of-the-art X/P dual-band lightweight digital array SAR system (X/P-DASAR) with a compact unit weighing less than 20 kg, which can be easily installed in a wide range of aircraft. This system adopted the integrated design of the X/P dual-band to realize the common aperture of the dual-band antenna, and employed digital beamforming technique to enable multiple radar modes such as large-swath scanning imaging, SAR high-resolution imaging, and detection of slow and small ground moving targets. Furthermore, it implements on-board real-time processing of currently multimode received data. X/P-DASAR serves as a test bed for the development, implementation, and testing of advanced radar technique applicable to earth observation imaging and moving target detection. In 2021, airborne test flights of the X/P-DASAR system were conducted in Meishan city, Sichuan Province. The data processing results verified the system’s excellent capabilities of 0.1 m high-resolution imaging and 4 km/h ground slow moving target detection.

This paper focuses on the study of a multi-frequency interferometric coherence characteristics analysis of typical objects for coherent change detection. Coherent change detection utilizes the phase difference between two or more SAR images to detect potential changes in the scene. It makes a difference in civilian and military applications. However, the relationship between the coherence of typical objects and SAR frequency has not been fully studied, which restricts the quality of the detection results. To address this problem, this paper conducts research on the relationship between the coherence of typical objects and SAR frequency, and the coherence characteristics are obtained through statistical analysis. In order to illustrate the relationship more clearly, the actual experimental data obtained by the DVD-InSAR system developed by the Aerospace Information Research Institute, Chinese Academy of Sciences, are utilized. The experimental results show that the coherence characteristics of typical objects are different, and this finding can provide strong support for developing change-detection applications.

This letter focuses on the detection of subtle human activity, from multipass airborne interferometric synthetic aperture radar (InSAR) images, of such activities causing absolute decorrelation between two acquisitions. These activities can be vehicle track, footprint, grazing, and human construction. The millimetric sensitivity of the interferometric phase makes it valuable for detecting such activities. It can bring a large value to civil and military applications. However, there are always high false alarms in the conventional detection method. To solve this problem, a human activity detection method based on the coherence matrix is approached in this letter. In the final part of this letter, a preliminary validation of the method is provided by processing actual multipass airborne InSAR data stacks acquired by the Aerospace Information Research Institute, Chinese Academy of Sciences. It is noted that the proposed method reaches reliable results in comparison with the ground truth.