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The performance of the polarimetric notch filter (PNF) algorithm based on the orthogonal projection technique has been widely recognized in the field of polarimetric synthetic aperture radar (PolSAR) ship detection. However, for detection problems in non-orthogonal target subspace and clutter subspace, using the orthogonal projection technique results in detection performance loss. In this letter, we propose a new ship target detector based on the oblique projection technique to deal with the condition that the target subspace and the clutter subspace are non-orthogonal. Since most sea clutter is inconspicuous in low-to-medium sea conditions, it is time-consuming to apply a fine target detector over the entire scene. Therefore, this letter proposes a keypoint detector based on the noncircularity and polarimetric scattering information to achieve fast localization of potential target regions. In general, we propose a novel two-step ship detection method for PolSAR data. The first step is to use the keypoint detector for potential target region localization, and the second step is to use the oblique projection detector to perform fine target detection on the potential target regions. Experiments on the synthetic and measured PolSAR data demonstrate that the proposed method is effective for ship detection. [ABSTRACT FROM AUTHOR]

The multipath in very high-frequency (VHF) radar will reduce the direction-of-arrival (DOA) estimation accuracy for the low-angle target following. Since the target and multipath signals have strong coherence in the spatial domain, it is challenging to distinguish them accurately. Especially in some terrain complex regions, various scattering media cause the multipath echo to exhibit multichannel and nonuniform energy distribution features. Therefore, the single-multipath DOA estimation methods will mismatch the actual signal, resulting in inaccurate DOA estimation. The current letter presents a new DOA estimation approach using a multiple scattering center model in complex terrain to solve the mentioned issue. In the presented method, multiple multipath is analogous to a single one based on the multipath signal’s spatial coherence. The equivalent model represents the DOA estimation problem with a parametric optimization problem, and accurate estimation results can be attained using the Newton optimization approach. Compared with the conventional sparse reconstruction method, the presented method is not restricted by the restricted isometry property (RIP) and employs a robust parameter estimation method to solve the angle super-resolution problem under the low signal-to-noise ratio (SNR). The experimental results reflect that the presented model and approach can efficiently promote the DOA estimation precision and calculational performance compared to conventional DOA estimation approaches. [ABSTRACT FROM AUTHOR]

Target recognition in SAR images was widely studied over the years. Most of these works were usually based on the assumption that the targets in the test set belong to a limited set of classes. In the practical scenarios, it is common to encounter various kinds of new targets. It is therefore more meaningful to study target recognition in open-world environments. In these scenes, it is needed to reject the unknown classes while maintain the classification performance on known classes. In the past years, few works were devoted to open set target recognition. Though the detection performance on unknown targets can be improved to a certain extent in the preceding works, most detection schemes are independent of a pretrained feature extractor, leading to potential open space risks. Besides, the model architectures are complicated, resulting in huge computational cost. To solve these problems, a family of new methods for open set target recognition is proposed. Targets indistinguishable from known classes are constructed by random sampling combination strategy. They are further sent into the classifier for feature learning. The original open-world environment is then transformed into a closed-world environment containing the unknown class. Moreover, the special implication of generated unknown targets is highlighted and used to realize unknown detection. Extensive experimental results on the MSTAR benchmark dataset illustrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Traditionally, inverse synthetic aperture radar (ISAR) imaging and target tracking are two separate and independent processes. ISAR imaging is usually achieved after data collecting and tracking for a long time, resulting in the problems of low imaging efficiency, information loss, and probing resource allocation difficulty. In this article, we proposed an integration method of tracking and imaging with wideband radar by constructing the relation among signal, data, and image domains, which can realize accurate tracking and high data-rate imaging at the same time. In this integrated imaging and tracking method, a complex-valued reference high-resolution range profile (HRRP) is generated and predicted by exploiting the relation among range-Doppler image, echo in time domain, and target's motion state. Then, a Bayes estimation model is built to extract range phase error between the predicted HRRP and the real-measured HRRP, and the Kalman filter can update the motion state. In addition, in order to increase the efficiency, the decentralized Kalman filter is also introduced to realize the subaperture parallel processing and data fusion in this article. Finally, the sequential motion compensation is carried out to realize accurate motion compensation and sequential imaging. The simulated and real-measured data confirm the proposed algorithm's robust imaging and tracking performance. Experimental results show that the proposed method has excellent efficiency and can simultaneously realize sequential imaging and accurate tracking. [ABSTRACT FROM AUTHOR]

In this letter, a novel method is proposed to rapidly simulate the multiaspect monostatic radar cross section of electrically large complex targets based on the shooting and bouncing ray method (SBR). The core of the method is to use the inheritance of the illumination to determine the illumination of the target surface, rather than independently simulating for each required aspect angle as in the traditional SBR method. To achieve this, the illumination variation on the target surface is summarized and the genetic illumination information is defined. The error of the method is also discussed and the multiple precalculation solutions is proposed to control the error. Different simulation examples show our method has good general applicability and great efficiency. Finally, a realistic aircraft is simulated at 10 GHz using the multiple precalculation solution. [ABSTRACT FROM AUTHOR]