Frequency modulation continuous wave (FMCW) synthetic aperture ladar (SAL) system can support the generation and processing of large bandwidth signals, which has strong capabilities in target detection, description and identification. However, frequency modulation nonlinearity of the transmitted signal has become a bottleneck problem that restricts the high-resolution ranging of FMCW SAL. This letter establishes an echo model with nonlinearity, and proposes a nonlinear phase estimation and compensation method based on Wigner-Ville distribution (WVD) with gradient rotation enhancement. Firstly, we establish the nonlinearity model of the internal calibration signal in time-frequency (TF) domain, and use WVD to calculate the time-frequency distribution (TFD). Secondly, the TFD is enhanced by rotating gradient vector, which also can eliminate noises and false components in the TFD. Then, the nonlinear phase of the transmitted signal is estimated by establishing a nonlinearity model in the TF domain. Finally, the residual video phase (RVP) filtering is introduced to eliminate the range-dependent nonlinearity and achieve nonlinearity correction of echoes at any range. Experiments and real data tests show that the method proposed in this letter can accurately estimate and correct the nonlinearity of the dechirp signal, which effectively improves the range resolution of FMCW SAL.

Airborne multichannel circular stripmap synthetic aperture radar (CSSAR)-ground moving target indication (GMTI) has drawn increasing attention in wide-area surveillance, reconnaissance and traffic monitoring due to its short revisit times. In this paper, a novel scheme for CSSAR-GMTI systems is proposed to offer high-resolution focusing of moving targets and enable efficient detection and accurate parameter estimation, which are ensured by integrating moving target imaging with a space-time adaptive processing clutter suppression step. The presented scheme develops a target imaging algorithm that forms SAR images focused on a particular 2-D motion parameter to maximize target signal energy and recover its high resolution. Moreover, benefiting from the suitable phase compensation designed in the 2-D frequency domain, moving targets can finally be properly focused in the SAR image without displacement and their parameters can be uniquely determined. Experiments on an emulated radar dataset are conducted to validate the effectiveness of the proposed scheme.

Synthetic Aperture Ladar (SAL) is a sensor that combines laser detection technology with synthetic aperture technology to achieve ultra-high-resolution imaging. Due to its extremely short wavelength, SAL is more sensitive to motion errors. The micrometer-level motion will affect the target’s azimuth focus. This article proposes an SAL motion compensation method based on Symmetric Triangular Linear Frequency Modulation Continuous Wave (STLFMCW) segmented interference, utilizing the characteristics of a triangular wave, to solve the problem of target azimuth defocusing. This article first establishes an STLFMCW echo signal model based on the SAL system under the influence of motion errors. Secondly, the radial velocity gradient along the azimuth direction is extracted using the triangular-wave-positive and -negative frequency modulation signals segmented interference method. Then, for the initial phase wrapping problem, the frequency spectral cross-correlation method is used to accurately estimate the initial radial velocity error. The radial velocity gradient is integrated along the azimuth to obtain the platform motion trajectory. Finally, the compensation functions are constructed to complete the echo Range Cell Migration (RCM) correction and residual phase compensation, resulting in a focused SAL image. This article verifies the practical effect of this method in eliminating motion errors using only one-period STLFMCW signal through simulation and real experiments. The quantitative results show that compared with the traditional method, the proposed method reduces the azimuth Peak Sidelobe Ratio (PSLR) by 8dB and the Integrated Sidelobe Ratio (ISLR) by 9 dB. This method has significant improvements and is of great significance for high-resolution FMCW SAL imaging.

Interferometric synthetic aperture radar (InSAR) is an integrated navigation technique that can be used for aircraft positioning and attitude retrieval, regardless of weather conditions. The key aspect of the entire system is interference fringe matching, which has not been extensively researched in existing literature. To address this gap, this paper proposes a terrain-feature-based interference fringe-matching algorithm. The proposed algorithm first extracts mountain line features from the interference fringes and identifies mountain branch points as key points for feature matching. A threshold is set to eliminate false detections of mountain branch points caused by phase mutation. Matching is then carried out by combining the mountain line features and curvature design feature descriptors of the area around a branch point. The proposed algorithm is verified using interference fringe data obtained from an actual flight experiment in Inner Mongolia, China, compared to a reference interference fringe dataset with errors. The results show that, under the condition of position error, the proposed algorithm yields 72 matching inliers with a precision of 0.103, a recall of 0.128, and an F1-Score of 0.144. Compared to traditional algorithms, our proposed algorithm significantly improves the problem of mismatch and opens up new possibilities for downstream interference fringe matching navigation technology. Furthermore, the proposed algorithm provides a new approach for remote sensing image matching using terrain features.

Inverse synthetic aperture ladar (ISAL) systems combine laser coherent detection technology with inverse synthetic aperture imaging methods, offering advantages such as compact size, long detection range, and high resolution. The traditional optical delay line technique is widely used in frequency-modulated continuous wave (FMCW) ISAL imaging systems, but its flexibility is limited, posing challenges for high-precision signal processing. Additionally, frequency modulation errors, atmospheric disturbances, and other errors inevitably affect image quality. Therefore, this paper proposes a signal processing method based on digital delay for FMCW ISAL, aiming to achieve the high-resolution imaging of targets across several kilometers. Firstly, the paper introduces the FMCW ISAL system. By introducing digital delay technology, it enables the flexible and real-time adjustment of reference signal delay. Next, to address the frequency offset issue caused by the introduction of digital delay technology, a preprocessing method for unified frequency shift correction is proposed to ensure signal consistency. Then, a set of internal calibration signal datasets is generated based on digital delay technology. Following this, a frequency modulation error iteration estimation method based on gradient descent is introduced. Without the need for target echo signals, the method accurately estimates the frequency modulation phase errors of both the transmitted and reference signals using only the internal calibration signals. Finally, this paper effectively decomposes the motion of the target, derives the echo model for the FMCW ISAL system, and constructs compensation functions to eliminate the intra-pulse Doppler shift and the residual video phase (RVP). Additionally, the Phase Gradient Autofocus (PGA) algorithm is used after two-dimensional imaging to eliminate the impact of atmospheric disturbances. We conducted two sets of experiments on point targets and surface targets to verify the effectiveness of error compensation in improving imaging quality. The results show that the two-dimensional resolution of point targets was optimized to 3 cm (range) × 0.6 cm (azimuth), while the resolution and entropy of the surface targets were both improved by 0.1. These results demonstrate that the proposed method effectively enhances target imaging quality and provides a new technical approach for high-precision signal processing in FMCW ISAL imaging.

This paper presents a new two-stage approach for suppressing strong clutter and detecting moving targets using scatterers’ spatial structure and signal similarity. Compared with the traditional strong clutter suppression methods, the proposed method considers both the spatial similarity and the channel correlation of the scatterers, effectively alleviating the false alarm probability and avoiding the missed detection problem caused via identifying strong moving targets as strong stationary clutter. Additionally, a detector is presented based on the linear degree of the radial velocity interferometric phase (LDRVP) to eliminate false alarms from isolated strong scatter points and the edges of strong scatterers. The experimental results of the X-band radar indicate the presented approach’s lower false alarm probability and superior robustness.