In this article, we propose a multichannel sea clutter model in a spaceborne early warning radar system and analyze the influence of the sea clutter motion characteristics on the space-time adaptive processing (STAP) performance. To establish a multichannel sea clutter model, the 3-D Gerstner wave model is applied to construct the sea surface. Then the Pierson–Moskowitz wave spectrum and the stereo wave observation project (SWOP) directional spectrum are combined to describe the amplitude distribution of waves in different frequencies and directions. At the same time, the two-scale model is applied to obtain the specific backscattering coefficients of sea clutter at different time and positions. In addition, breaking waves are added in sea clutter returns with the form of false targets. Finally, the space-time distribution characteristics of sea clutter in a spaceborne multichannel array system and the influences of sea clutter under different wind speeds and directions on STAP performance are analyzed based on the simulation processing results. Processing results of some real-measured radar data are also exhibited to verify the theoretical analyses.

When an early warning radar installed in a spaceborne platform works in a down-looking mode to detect a low-altitude flying target, the severely broadened main-lobe clutter cannot be ignored, which will cause the deterioration of the moving target detection capability. To deal with this problem, a space–time adaptive processing (STAP) technique is proposed for effective clutter suppression based on the spatial–temporal 2-D joint filtering. However, the full-dimensional optimal STAP encounters the challenges of high computational complexity and large training sample requirement. Therefore, the dimension-reduced STAP technique becomes necessary. This article proposes a novel dimension-reduced STAP algorithm based on spatial–temporal 2-D sliding window processing. First, several sets of spatial–temporal data are obtained by using spatial–temporal 2-D sliding window. Then, for each set of data, the 2-D discrete Fourier transform is performed to transform the echo data into the angle-Doppler domain. Finally, jointly adaptive processing is performed to realize the clutter suppression. Compared with the conventional STAP algorithms, the improvements of this method over the existing methods are: 1) the proposed method requires fewer training samples due to the 2-D localization processing and 2) the proposed method can obtain the better clutter suppression performance with lower computational complexity. The feasibility and effectiveness of the proposed algorithm are verified by both simulated and real-measured multichannel surveillance radar data.

In synthetic aperture radar (SAR), long integration time may induce range migration and Doppler frequency migration of a received signal, which may degrade the SAR imaging performance of ground moving targets. Most of the conventional algorithms deal with the problems of range migration and Doppler frequency migration based on parameter searching. However, the exhaustive searching of target motion parameters may result in heavy computational burden. To avoid this problem, this paper proposes a new imaging method for ground moving targets without target motion parameter estimation. First, Keystone transform is applied to correct the range walk. Second, range curvature is compensated by the matched filtering function. Third, Doppler frequency migration is compensated via multiplying the data in range- and azimuth-time domains by its reversed conjugate data according to the equal interval sampling of the azimuth slow time, which avoids the searching procedure for target motion parameter estimation. Finally, the signal energy will be well accumulated in the range-Doppler domain, and thus, the moving targets can be efficiently recognized in the focused image. The major advantage of the proposed method is that it can obtain well-focused images of all targets in one processing step without target motion parameter estimation; thus, it is computationally efficient. Both simulated and real data processing results are used to validate the effectiveness of the proposed method.

In this paper, a new algorithm is presented to image ground moving targets in a synthetic aperture radar (SAR) system based on range frequency reversal transform-fractional Fourier transform (RFRT-FrFT). In this algorithm, a range compressed signal is initially transformed into the range frequency domain and then RFRT is proposed to directly compensate the range migration via multiplying the signal in the range frequency domain by its reversed data according to the equal interval sampling of range frequency variable, which can significantly decrease the computational complexity in target envelope migration elimination. Then, FrFT is applied to accomplish the target motion parameter estimation after range migration alignment. Finally, a ground moving target is well focused after motion compensation. The effectiveness of the proposed algorithm is validated by both simulated and real SAR data.

Synthetic aperture radar (SAR) can operate around the clock and in all weather, and therefore high-resolution SAR images have been frequently applied for ship inspection. However, current ship target detection and identification methods have limited detection accuracy and lead to missing detection of small targets due to speckle noise caused by the imaging principle of SAR imagery and complex nearshore interference. Therefore, this paper proposes an improved YOLOv5 method to address the problem of low accuracy in multi-ship target detection tasks in complex scenes. The developed scheme enhances the ship target detection performance while reducing the number of parameters. Specifically, first, we improve the size of the input SAR images and optimize the anchor frames of ship targets in the training dataset to locate small target ships more accurately. Then, symmetric pyramidal non-local block(APNB) and Sim attention mechanism (SimAM) are introduced to reduce near-shore background interference. Additionally, to make the C3 module output richer and with more feature information, channel shuffling is performed after the C3 output to enhance the information exchange between channels. Finally, to reduce the number of parameters and computational cost during model training, the normal convolution in the NECK part is replaced with Ghost convolution. The index F1 of the proposed method on the High-Resolution SAR Image Dataset (HRSID) and SAR Ship Detection Dataset (SSDD) reaches the highest of 91.3% and 95.8%, respectively. MAPs (0.5:0.95) for the two datasets are both the highest, which are at least 2% higher than the suboptimal method. In selected specific inshore scenes, the ship detection performance of the proposed method outperforms current advanced methods for multiscale ships. It is shown that the proposed method can extract ship features effectively in complex scenes and its effectiveness is further validated on the large scene AIR-SARShip-1 dataset.

In a multichannel synthetic aperture radar (SAR) system, because of the target uncooperative motion, a ground moving target (GMT) is usually smeared, distorted, and shifted in an SAR image. In this article, a novel approach for multichannel SAR-GMT indication (GMTI) processing is proposed. The main innovations of this method are that a GMT can be well refocused and relocated since the target high-order Doppler parameters can be precisely estimated based on a high-order polynomial phase signal (PPS) model, and the target statistical amplitude and phase information is jointly applied to improve the radial velocity estimation robustness. Compared with the current SAR-GMTI algorithms, the improvements of this method over the existing methods are: 1) the topography interferometric phase can be effectively compensated by applying an adaptive 2-D spectrum filtering technique via iterative processing; 2) a GMT can be well imaged since the target Doppler chirp rate and the quadratic chirp rate can be well estimated via the 2-D coherent integration in the time–frequency plane; and 3) a GMT can be precisely relocated into its original position by applying the generalized amplitude and phase weighting technique. Real-measured SAR data processing results are presented to validate the effectiveness and feasibility of the proposed method.