Clutter suppression is a challenging problem for passive bistatic radar systems, given the complexity of actual clutter scenarios (stationary, time-varying and fractional-order clutter). Such complex clutter induces intense sidelobes in the entire range-Doppler plane and thus degrades target-detection performance, especially for low-observable targets. In this paper, a novel method, denominated as the batch version of the extensive cancellation algorithm (ECA) in the frequency domain (ECA-FB), is presented for the first time, to suppress stationary clutter and its sidelobes. Specifically, in this method, the received signal is first divided into short batches in the frequency domain to coarsen the range resolution, and then the clutter is removed over each batch via ECA. Further, to suppress the time-varying clutter, a Doppler-shifted version of ECA-FB (ECA-FBD) is proposed. Compared with the popular ECA and ECA-B methods, the proposed ECA-FB and ECA-FBD obtained superior complex clutter suppression and slow-moving target detection performance with lower computational complexity. A series of simulation and experimental results are provided to demonstrate the validity of the proposed methods.

A new synthetic aperture radar (SAR) image segmentation method based on a maximization of posterior marginals (MPM) algorithm with feature extraction and context model is proposed in this letter. First, Gabor wavelet and texture descriptor are used to extract features, which enhance intraclass similarities and interclass differences. Second, the number of regions within the same class is reduced in order to improve the reliability of the regional statistical characteristics. Finally, the MPM of each region combined with the context model is calculated by considering both the intralayer correlation and interlayer correlation. The experimental results show that the proposed method is efficient and effective for SAR image segmentation.

In this paper, the possibility of improving target detection performance in passive bistatic radar by exploiting a frequency agile (FA) signal is investigated, namely frequency agile signal-based passive bistatic radar (FAPBR) coherent integration. Since the carrier frequency of each pulse signal is agile, FAPBR coherent integration suffers from the problems of random range and Doppler phase fluctuations. To tackle these challenges, a novel FA signal coherent integration target detection scheme for PBR is proposed. In particular, the phase quadratic difference principle is presented for eliminating Doppler phase hopping. Then, frequency rearrangement is adopted to compensate for random range phase fluctuation while obtaining the high-range-resolution profiles (HRRPs) of the detecting target. Further, we innovatively present a sliding-range ambiguity decoupling (S-RAD) method to remove the range ambiguity effect in the case of the high pulse repetition frequency (HPRF). Compared with the existing methods, the proposed method can effectively mitigate Doppler phase hopping without requiring prior target velocity information, offering improved coherent integration performance in frequency agile signals with reduced computational complexity. Moreover, it successfully corrects the range ambiguity issue caused by HPRF. Finally, a series of simulation results are presented to demonstrate the effectiveness of the proposed algorithm.

While spin-orbit torque magnetic random access memory (SOT-MRAM) have shown huge potential for building next-generation embedded memory due to their attractive characteristics, the read reliability remains one of the critical concerns precluding its further application. In this article, we propose a dynamic time-domain sensing (DTDS) scheme for SOT-MRAM, in which the conversion threshold voltage of voltage-to-time converter (VTC) can be dynamically changed according to the data stored in SOT-MRAM, so as to lengthen the time difference of the VTC output signals. The proposed DTDS scheme can achieve a significant improvement in sensing margin of time-domain, thereby increasing the read reliability and reducing bit error rate (BER). Applying it to a 128 $\times$ 128 SOT-MRAM using 28 nm CMOS technology, an average read BER of 2.84 $\times$ 10 $^{-\text{10}}$ is achieved, which is greatly reduced compared to the conventional time-domain sensing scheme.

This paper considers the range migration problem for realizing the long-time coherent integration of a weak target in passive bistatic radar (PBR). In particular, we analyze the causes of range migration in PBR system in terms of the detection characteristics of continuous wave. We also propose a novel range migration correction method in the frequency domain, where stretch processing and chirp-z (CZT) transform are adopted to eliminate the range migration and thus obtain long-time coherent integration of the target's energy. Numerical results are presented to demonstrate the effectiveness of the proposed method.

A novel phase retrieval method for hard X-ray in-line phase contrast imaging is presented in this paper, which is based on a parallel hybrid genetic algorithm. Different from the tradition numerical algorithm, our approach is a parallel hybrid intelligent method. Some techniques, such as parallel computing, simulated annealing selection and elitist migration, are all combined together with the genetic algorithm to accelerate the convergence and improve the quality of the final output. The proposed method is validated by numerical simulations on MATLAB platform. Experimental results show that the parallel hybrid GA is a satisfying solution for phase retrieval because of its fast convergence and high speed-up.