The challenge in the imaging of high-squint-mode synthetic aperture radar (SAR) mounted on maneuvering platforms is azimuth dependence both range migration and focusing parameters (the frequency-modulation rate higher order coefficients), which are caused by walk correction acceleration. In to accommodate dependence, a modified subaperture algorithm proposed. Based fact that times corresponding same Doppler frequency different for targets gate, after making blocks domain, azimuth-dependent...

In this paper, we consider a passive radar system that estimates the positions and velocities of multiple moving targets by using OFDM signals transmitted totally un-coordinated un-synchronizated illuminator receivers. It is assumed data demodulation performed separately based on direct-path signal, error-prone estimated symbols are made available to receivers, which estimate in two stages. First, formulate problem joint estimation delay-Doppler reflectors errors, exploiting types sparsities...

A distributed configuration is a promising realization of tomographic synthetic aperture radar (TomoSAR) 3-D imaging. It able to implement single-pass imaging in very short time and, hence, outperforms the traditional time-consuming multipass TomoSAR. also single-platform TomoSAR by achieving higher resolution elevation forming much larger spatial baseline. However, there has been little research reported on so far. In this article, we, for first time, experimentally demonstrate great...

Low-inclined elliptical orbits are recommended for geosynchronous synthetic aperture radar (GEO SAR) to map the regions of interest at middle latitudes. However, radius variation such orbit results in a time-variant nadir interference and slant range illuminated regions. These factors shorten available imaging time specific pulse repetition interval (PRI), which may be even shorter than required integration time. Besides, squint mode widely used GEO SAR brings nonorthogonal nonuniform ground...

Radar is an electronic device that uses radio waves to determine the range, angle, or velocity of objects. Real-time signal and information processor important module for real-time positioning, imaging, detection recognition targets. With development ultra-wideband technology, synthetic aperture processing radar coverage, accuracy resolution have been greatly improved, especially in terms one-dimensional (1D) high-resolution detection, tracking, recognition, two-dimensional (2D) imaging...

Doppler centroid is a key focusing parameter of beam sharpening (DBS) imaging. According to the locked relationship between error and image entropy, minimum-entropy estimator (MEDE) proposed. The algorithm breaks conventional algorithms' assumption that shape echo signal's power spectrum symmetrical, proposed method can circumvent problem low estimation precision using algorithms process signal from high-scene contrast. new based on entropy minimization has high in case low- MEDE been...

Synthetic Aperture Radar (SAR) ship detection has been a research hotspot and is significant for marine surveillance. Traditional constant false alarm rate (CFAR) detector the disadvantages of high poor adaptability. Deep learning provides unique solution SAR detection. However, traditional deep network cannot reach very thus accuracy limited, training speed slow. In this paper, ResNet with higher faster applied to train model. Moreover, transfer combat small dataset. The proposed method...

Existing ship inverse synthetic aperture radar (ISAR) imaging algorithms are not applicable, when the signal-to-noise ratio (SNR) is low, for translational motion that cannot be well compensated by existing algorithms. To achieve ISAR with low SNR, a algorithm based on generalized radon-Fourier transform (GRFT) proposed in this paper. Considering only rotational but also between and ship, uses GRFT to simultaneously compensate time-variant range envelopes Doppler phase. Thus, signal...

The compressed sensing (CS)-based synthetic aperture radar (SAR) imaging methods have emerged as the standard approach to obtain super-resolution (SR) SAR images and achieve extraordinary performances. However, they face three challenges. First, this kind of method is mainly based on point scattering model not suitable for characterizing line-segment-scattering surface-scattering features distributed targets. Second, hyperparameters in these are hard tune optimal values. Third, due a large...

Unmanned-aerial-vehicle-based (UAV-based) ultrawideband and ultrawidebeam (UWB) synthetic aperture radar (SAR) is very sensitive to atmospheric turbulence suffers from serious 2-D space-variant motion errors (SVMEs) caused by the ultrawide beam frequency-dependent phase ultrawideband. This article proposes an autofocus approach for UAV-based UWB SAR data based on quasi-polar grid fast factorized backprojection (FFBP) imaging framework, multiple subband local (MSBLA), trajectory deviation...

The Doppler rate of geosynchronous synthetic aperture radar (GEO SAR) may be positive, negative, or even zero at different orbital positions. When the is near some special positions, range cell migration cannot corrected in (RD) domain by traditional frequency algorithms. To solve this problem, a modified algorithm based on optimal quadratic factor compensation, including phase and envelope proposed paper. First, compensation two-dimensional (2-D) time introduced to expand folded azimuth...

To realize real-time imaging for the spaceborne synthetic aperture radar (SAR) using chirp scaling (CS) algorithm, high generation rates of phase factors and heavy computation loads are unavoidable. For example, updating continuously in 2-D time or frequency space is difficult generating imaging. solve this problem, a modified CS algorithm based on regionally proposed. Moreover, conventional floating-point arithmetic unaffordable onboard. Therefore, fixed-point processing adopted. In...

Phase autofocus is a significant step in translational motion compensation for inverse synthetic aperture radar (ISAR) imaging. Among the existing methods, contrast maximization-based algorithms are superior accuracy and robustness. However, maximum methods parametric, which significantly affects their convergence speed and, some cases, limits applicability. In this paper, novel non-parametric ISAR algorithm based on Newton's method proposed to inherit high level of robustness contrast-based...

Current image fusion methods are primarily designed for infrared and visible images under normal illumination conditions. In multi-scene environments, where conditions such as varying lighting, weather, or scene characteristics present, existing face challenges, particularly low-light Due to the severe degradation of in scenarios, these struggle with insufficient feature representation, poor quality, knowledge loss during task switching. order solve above problems, this paper proposes a...

Airborne synthetic aperture radar (SAR) raw data are affected by motion errors due to atmospheric turbulence and aircraft properties, this makes compensation (MOCO) an essential step. In order decrease the influence of variable information, a kind MOCO approach called azimuth-subaperture processing is widely used, which causes azimuth-signal aliasing in squint SAR mode. Usually, can be ignored, since its effect on final results not worth mentioning. However, when angle grows, it becomes...

Applying a continuous varying pulse interval (CVPI) sequence is of significance for an extremely high-resolution (EHR) spaceborne sliding spotlight synthetic aperture radar (SAR) complete data acquisition. An optimum CVPI should be the one leading to minimum movement echoes interest in train. However, such optimization can hardly conducted using traditional timing diagram. Aiming at solving this problem, article introduces new graphic tool, referred as strip layering diagram, achieve EHR...

Due to the advantage of flexible and rapid deployment, unmanned aerial vehicle (UAV)-based synthetic aperture radar (SAR) tomography (TomoSAR) is a promising technology in 3-D urban mapping. The long baseline indispensable for P-band SAR systems achieve high elevation resolution. It will introduce two problems. On one hand, unavoidable spatial decorrelation brings serious phase noise sidelobes imaging. other noticeable image distortion fails registration TomoSAR data stack (TDS)...

In this paper, a fall detection method is proposed by employing deep learning and multi-sensors fusion. Continuous wave radar optical cameras are used simultaneously to capture human action information. Based on the abstraction of both microwave characteristics captured information, multiple convolutional neural network (CNN) realize information training recognition. Due fusion multi-sensor overall performance system can be improved remarkably. Detailed experiments given validate method.