A novel semantic Minimum Bayes ternary hypothesis detector based on the Rayleigh distribution is presented to decrease detection false alarm rate of synthetic aperture radar image. The method not only employs the strong scattering features of the target which is used in constant false alarm rate (CFAR) but employs the shadow features of the target which is used in the Power Ratio detector. Furthermore, target, shadow, and clutter regions are merged into the ternary image to estimate Rayleigh distribution parameters and weights. Meanwhile, the semantic relationship between the strong scattering features and the shadow features is established to partly reduce the false alarm targets. By the experiments on the Mini-SAR image of the 4-in resolution, it is shown that our method outperforms the semantic CFAR method and CFAR algorithm by a much lower false alarm rate.

The holographic subsurface radar (HSR) is recognized as an effective remote sensing modality for the detection of shallowly buried objects with a high-resolution image in plain view. However, subsurface detection with HSR is prone to be impaired by clutter contamination, which often obscures the target response. In this letter, a novel clutter mitigation method combining singular value decomposition (SVD) and response cross correlation analysis is presented. The proposed method first applies SVD to decompose the radar data matrix to a number of singular components. Furthermore, the signal cross correlation characteristics are analyzed to demonstrate that the variance of left singular vectors is directly proportional to the target proportion in radar data. Then, target and clutter subspaces can be identified by maximizing the defined weighted target-to-clutter ratio (WTCR). Results of numerical simulation and laboratory experiments corroborate the effectiveness of the proposed method in reducing clutter while preserving the target image.

Holographic subsurface radar (HSR) is a promising geophysical electromagnetic technique to detect shallowly buried objects due to its high lateral resolution. However, the subsurface inspections and visualization of buried targets are prone to be impaired by strong clutter from the nonplanar surface reflections. In this article, a clutter mitigation method using dual-frequency cancellation and sparse feature enhancement is proposed for HSR data to distinguish the targets from background. The radar signals are received at two distinct frequencies under certain conditions to calculate the strong surface reflections. After cancellation of the estimated surface, a modified$\ell _{1}$regularization is utilized to further mitigate the residual clutter and highlight the target signature. The effectiveness of the proposed method is evaluated on both numerical simulation and radar signals collected from real HSR systems. The visual and quantitative results demonstrate that the proposed method successfully removes the nonplanar surface clutter with the targets preserved.

The holographic subsurface radar (HSR) has been a promising geophysical electromagnetic technique for detecting shallowly buried targets with high lateral resolution image. However, the radar images are considerably interpreted by strong reflections from the rough surface and inhomogeneity in media of interest. In this article, we focus on mitigating the clutter in HSR applications using a learning-based approach, which requires neither prior information regarding the penetrable medium characteristics nor analytic framework to describe the through-medium interference. The generative adversarial network (GAN) with attentive subspace projection is developed to remove the clutter and recover the target image. The subspaces containing target response are selected with the multi-head attention preliminarily. Then, the generative network will further focus on the target regions and the discriminative network will assess the generated results locally and globally. Experiments using real data were conducted to demonstrate the effectiveness of our approach. The visual and quantitative results show that the proposed approach achieves superior performance on removing clutter in HSR images compared with the state-of-the-art clutter mitigation approaches.

Geosynchronous (GEO) orbit and low-earth-orbit (LEO) in imaging have many differences, especially for relief of undulating three-dimensional(3D) terrain, the imaging errors caused by target elevation in two orbits of different altitudes are also diverse. The error caused by terrain elevation under the LEO SAR is negligible, and in GEO SAR the error will cause serious azimuth defocusing. This paper focuses on the error caused by topography elevation in LEO and GEO SAR respectively. Firstly, the SAR imaging geometric model including terrain elevation is established. Then, the source of error caused by terrain elevation and its influencing factors are analyzed. Finally, the error changes of the two orbits are analyzed, and the correctness of the proposed viewpoint is verified by experiments.

VideoSAR (video synthetic aperture radar) can provide continuous surveillance over a specific region, and shadow can be utilized to detect moving target. However, feature variations (unstable scattering properties and continuous motion) may seriously damage the precision of registration. Speeded Up Robust Feature (SURF) is one of the most popular method for feature detection and SAR image registration. So in this paper, a robust image sequence registration algorithm for videoSAR is proposed based on the combination of SURF and inter-frame processing. SURF is firstly introduced to videoSAR registration, whereas the continuous feature variation through the entire image sequence, showing a severe loss of robustness . Aiming at this defect, SURF and the idea of inter-frame processing are integrated and forming a novel algorithm. Simulation experiments underline the effectiveness and robustness of the proposed method in videoSAR image sequence registration.

Phase synchronization is a key problem which has to be carefully considered in the distributed radar systems. In this letter, the use of a continuous duplex phase synchronization method for the distributed frequency modulated continuous wave synthetic aperture radar system is investigated. The bistatic raw signal model containing the phase difference due to the spatially separated oscillators is introduced. The continuous duplex phase synchronization procedure is proposed later and the synchronization method performance is predicted.

Synthetic Aperture Radar (SAR) system of high frequency, high resolution and high frame rate is one of the hot research areas. At present, the analysis of vibration error influence mainly embarks from the theoretical derivation, and simulated in level model. In order to accurately analyze the influence of high frequency vibration to high frequency SAR, it is necessary to simulate in signal level. Due to the short wave length of high frequency SAR, impact of high frequency vibration which is almost negligible to the conventional SAR of microwave band must be finely processed. Phase Adjustment by Contrast Enhancement (PACE) is a better SAR imaging autofocusing algorithm in the case of low Signal Noise Ratio (SNR), which can precisely estimate high frequency phase errors. In actual implementation, interpolation method is an effective means to improve the efficiency of the algorithm.

HRWS-SAR steers the antenna to increase the synthetic aperture which causes the radar changes beam squint angle gradually. The squint angle increases with the demanding of the resolution and swath width. With the squint increasing, the relative velocity between radar and lighting swath may reach several km/s. It causes the intra-pulse modulation on the echo. The traditional pulse compressing under the stop-go-stop assumption has bad performance including resolution decrease and PSLR increase. The paper established the echo model. The chirp rate is slightly changed because of the relative velocity. And velocity compensation method is put forward. The experiment results show that the pulse is well compressed. The PSLR and the resolution are restored to normal level.

This paper proposed an innovative bistatic radar system, named as GEO-UAV bistatic circular synthetic aperture radar (BCSAR). In GEO-UAV BCSAR, the geostationary satellite serves as the transmitter, while the receiver is mounted on the UAV platform moving along a circular trajectory. Combining the technical advantages of GEO SAR and that of UAV platform, GEO-UAV BCSAR benefits from low-cost, high operational flexibility and 3-D imaging ability. This paper introduced its system concept, and discussed its imaging ability and technical challenges. It is shown that the proposed GEO-UAV BCSAR could be able to provide a potential alternative for future remote sensing missions.

When bistatic synthetic aperture radar (SAR) works in alternating bistatic/ping-pong mode, it can perform phase referencing without a synchronization link between different satellites. The key to this is to extract a compensation phase from the bistatic echoes, including oscillator phase differences. An echo-domain phase synchronization algorithm using the correlation of bistatic echoes is proposed. Because of its larger equivalent synchronization frequency, the echo-domain algorithm has higher phase synchronization accuracy than the algorithm in the image domain. Experiments using simulated bistatic echoes with real single-stripmap SAR echo validate the proposed echo-domain phase synchronization algorithm.

To address the new requirements for InSAR raw-signal simulation for hardware-in-the-loop simulation application, a real-time raw-signal simulation algorithm with high accuracy is proposed. The raw signal is expressed as the convolution of the transmitting signal and the scene modulation signal (SMS), and the convolution is then implemented using the fast Fourier transform. The SMS is calculated by the position approximation in the time domain, and an interpolation technique is used to maintain the accuracy of the fast approximation algorithm. The SMS is filtered to the radar sampling frequency for real-time implementation. The approximation error of the fast algorithm is analyzed quantitatively to obtain the minimum interpolation factor. Ground-based hardware-in-the-loop simulation results are provided to validate the algorithm.

Due to the separation of the radar transmitter and receiver, the channel mismatch, the time and phase synchronization error between synthetic aperture radar (SAR) central electronic equipments (CEE) is the key problems of spaceborne distributed SAR system compared with the traditional single-satellite double pass interferometric SAR (InSAR) system, which has to be considered in the SAR system design, index allocation, integration and testing, verification and validation. A hardware-in-loop simulation and evaluation approach is presented for the influence analysis of CEE payload on the InSAR performance. The hardware-in-loop simulation system includes the master and slave CEE payloads, the time and phase synchronization prototypes, the on-board computer simulator, the SAR target echo signal simulator (TESS) and other auxiliary equipments. For obtaining the influence of the error source on InSAR performance, a hardware-in-loop simulation and evaluation approach based on different hardware configuration is adopted. The experiment results validate the theoretical analysis and computer-based simulation results, and show the feasibility of the time and phase synchronization scheme, which is meaningful for the implementation of the spacebome distributed SAR system.

As adoption of the newly standardized H.264 becomes increasingly more widespread, efforts must be made to transcode video from earlier standards, such as MPEG-2, to the H.264 format. One aspect of transcoding is the conversion from the discrete cosine transform (DCT) used in MPEG-2 to the integer-based DCT of H.264, the integer cosine transform. By investigating the structure of the transform kernels, two efficient schemes are introduced to convert an 8 times 8 DCT block into its corresponding four 4times4 integer cosine transform block8 times 8 DCT block into its corresponding four 4times4 integer cosine transform blockss. An analysis of computational complexity shows a reduction of up to 42% in multiplications over existing conversion schemes, while simulations of the conversion system with pre- and post-quantization show that the proposed methods yield high fidelity in terms of peak signal-to-noise ratio. Further approximation of matrix coefficients in the second proposed method yields additional conversion schemes which require no multiplications. These also provide comparable quality with fewer operations than existing schemes. Thus, the proposed transform conversion methods can potentially contribute to efficient transcoding systems.

According to fractal ocean surface model, electromagnetic scattering model under Kirchhoff approximation and the raw signal simulation procedure of dynamic scene based on time domain, spaceborne synthetic aperture radar (SAR) raw signal of ocean scene is generated. The SAR images obtained from the echo of both simple cosine wave and complex fractal ocean surface are in accordance with the tilt modulation and the velocity bunching theoretically, and also with the statistical properties of real ocean SAR images, which validate the simulation procedure. The raw signal could be the input data of studying along-track InSAR (ATI) for ocean current measurements.

Variants of the discrete cosine transform (DCT) have been selected for different image/video compression standards, and fast conversion algorithms between these transforms are needed. In this paper, conversion between an 8×8 DCT block, used in MPEG-2, and its corresponding 4×4 integer DCT blocks, used in H.264, is studied. By investigating the structure of the two transform kernels, a DCT decomposition scheme is adopted in development of the fast conversion algorithm. Analysis of the performance of this conversion scheme shows that the proposed scheme provides over 45% computation savings on multiplications, as compared to an existing scheme, while maintaining high fidelity in terms of PSNR.

For sketch-based retrieval of images, characterization and comparison of the geometrical structure (shape) information is of great importance. In this paper, a directional-projection-based sketch image retrieval system (DPSIR) is proposed. In the DPSIR system, efficient filter banks are adopted to decompose the image into directional subbands in order to capture edges at different orientations. Through projection of each subband into a pair of orthogonal profiles, the shape information is compactly captured by identifying the structure of each one-dimensional projection profile. By comparing the projection profiles of the sketched image with those in an image database, a set of images with shapes similar to the sketched images are retrieved. Experiments using the DPSIR system on an MPEG-7 shape database yield high retrieval rates.

Two statistical models for color texture retrieval based on a hidden Markov model (HMM) in the contourlet domain are described in this paper. Through a contourlet transformation, each color component of an image is decomposed into a set of directional subbands with texture details captured in different orientations. By exploiting inter-scale dependencies and in-band spatial dependencies, the distribution of the coefficients in each subband triplet (subbands of three color components at the same scale with the same orientation) can be estimated using a vector hidden Markov model. The Kullback-Leibler distance (KLD) is used to measure the difference between the distributions of query texture images and those of images in the database. The experimental results show the proposed retrieval systems yield high retrieval rates and better visual quality as compared with previous methods employing hidden Markov models for luminance component alone.