Multichannel Synthetic Aperture Radar Research Articles

Unambiguous Imaging of Static Scenes and Moving Targets with the First Chinese Dual-Channel Spaceborne SAR Sensor.

Multichannel synthetic aperture radar (SAR) is a breakthrough given the inherent limitation between high-resolution and wide-swath (HRWS) faced with conventional SAR. This paper aims to obtain unambiguous imaging of static scenes and moving targets with the first Chinese dual-channel spaceborne SAR sensor. We propose an integrated imaging scheme with the dual-channel echoes. In the imaging scheme, the subspace-based error estimation algorithm is first applied to the spaceborne multichannel SAR system, followed by the reconstruction algorithm prior to imaging. The motion-adapted reconstruction algorithm for moving target imaging is initially achieved with the spaceborne multichannel SAR system. The results exhibit an effective suppression of azimuth ambiguities and false targets with the proposed process. This paper verifies the accuracy of the subspace-based channel error estimator and the feasibility of the motion-adapted reconstruction algorithm. The proposed imaging process has prospects for future HRWS SAR systems with more channels.

Fast channel phase error calibration algorithm for azimuth multichannel high-resolution and wide-swath synthetic aperture radar imaging system

The configuration of multiple uniformly spaced channels in azimuth can achieve high-resolution and wide-swath images for synthetic aperture radar (SAR) systems. The unambiguous Doppler spectrum can be reconstructed via digital beamforming (DBF) techniques in the azimuth multichannel SAR system. However, the performance of DBF deteriorates significantly because of the inevitable channel errors in practical applications. Since the SAR antennas are generally unweighted in azimuth, the power of the SAR signal is symmetrically distributed around the Doppler centroid in the azimuth frequency domain. Based on this observation, the covariance matrix of multichannel output in the range-Doppler domain can be regarded as a real matrix when there is no existence of channel errors and the correction of the baseband Doppler centroid is applied. Consequently, we propose a fast calibration algorithm to calculate channel phase errors. The proposed method can acquire the estimation of phase errors directly from the covariance matrix. Thus, the proposed method has the properties of high robustness and low computation load. Theoretical analysis and experiments validate the performance and the efficiency of the proposed algorithm.

Suppression of Azimuth Ambiguities of Strong Point-Like Targets for Multichannel SAR Systems

Multichannel synthetic aperture radar (SAR) signal reconstruction methods can effectively suppress azimuth ambiguities and achieve high-resolution wide-swath imaging. However, due to the characteristics of the practical antenna patterns, there exist non-bandlimited Doppler spectra, which will result in residual azimuth ambiguities, especially for strong targets. This letter presents a novel method for the suppression of the azimuth ambiguities of the strong point-like targets. First, we find out the positions of the strong point-like targets from the multichannel reconstructed SAR image. Then, we locate the ambiguous range history of each strong point-like target. Finally, the ambiguous components in the range history are filtered out by an orthogonal projection method. Therefore, the spectra of the strong point-like targets will be converted into the bandlimited spectra, and then, the azimuth ambiguities can be effectively suppressed by the conventional multichannel SAR signal reconstruction methods. Theoretical analysis and experiments demonstrate the feasibility of the proposed methods.

Moving Targets Detection Capacities Improvement in Multichannel SAR Framework

When using multichannel synthetic aperture radar (MSAR) to perform moving target detection, the coherence between the received signals is closely linked to the detection capacities of the system. In airborne MSAR context, because of the platform movement, the antenna patterns, as well as the phase shifts between the channels, evolve in different ways during the integration time. In this paper, these dissimilarities are shown to cause a degradation of coherence, and hence of detection capacities. A method to enhance the coherence is then developed. This method is based on the estimation of the steering vector. It is applied on two sets of real data, and the obtained results validate the method.

Clutter suppression and moving target imaging approach for multichannel hypersonic vehicle borne radar

In this paper, a clutter suppression and ground moving target imaging algorithm is proposed for the hypersonic vehicle (HSV) borne multichannel synthetic aperture radar (SAR) system. Different from the traditional horizontal flight radar platforms, the HSV-borne radar platform is with a complex movement, and typically has a skipping trajectory. Therefore, the clutter suppression and imaging operations are difficult to implement. To deal with this problem, a descending stage signal model of multichannel SAR system is presented and studied for the HSV-borne radar. Then, the clutter and moving target echoes are transformed into the azimuth frequency domain. Considering that there exists a phase difference between clutter and the moving target, the clutter suppression approach is implemented with a series of spatial domain filters. After that, the moving target is focused based on the keystone transform. In addition, the performance analyses and related issues of the proposed method are presented. Finally, some simulation experiments are taken to validate the effectiveness of the proposed method.

Robust phase mismatch calibration for multichannel sliding spotlight SAR imaging​​​

ABSTRACTThis paper investigates the aspect of phase mismatch calibration for multichannel in azimuth synthetic aperture radar (SAR) operating in the sliding spotlight mode. In conventional multichannel stripmap SAR systems, it is assumed that all the sub-aperture antenna phase centers are along the sensor track during system operation. However, in the multichannel sliding spotlight mode, the utilization of beam progressive sweeping in azimuth causes movement of the antenna electromagnetic phase centers along with the time-variant beam squinted angle, which brings space-varying phase error between different channels. In this paper, a calibration method based on the imaging geometry was developed to address this problem, which needs no iteration or block-wise processing. Processing with experimental data obtained from a C-band dual-channel sliding spotlight airborne SAR shows effective channel phase mismatch cancellation.

Robust Channel Phase Error Calibration Algorithm for Multichannel High-Resolution and Wide-Swath SAR Imaging

High-resolution and wide-swath synthetic aperture radar (SAR) imaging can be achieved by the azimuth multichannel system. The minimum variance distortionless response (MVDR) beamformer can be utilized to suppress azimuth ambiguities. However, the presence of channel phase errors significantly deteriorates the performance of the azimuth multichannel SAR system. Instead of employing subspace techniques, this letter proposes a robust channel phase error calibration algorithm via maximizing the MVDR beamformer output power. Compared with the conventional subspace-based calibration methods, there is no redundancy of channels required to estimate the subspaces in the proposed algorithm. Also, the proposed algorithm is relatively robust, because it avoids the subspace swap phenomenon, which probably takes place at low signal-to-noise ratios for the subspace techniques. Moreover, the proposed method has the advantage of estimating the channel phase errors without covariance matrix decomposition, which reduces the computation load. The simulation experiments and the real data processing validate the effectiveness of the proposed calibration method.

An ML-Based Radial Velocity Estimation Algorithm for Moving Targets in Spaceborne High-Resolution and Wide-Swath SAR Systems

Multichannel synthetic aperture radar (SAR) is a significant breakthrough to the inherent limitation between high-resolution and wide-swath (HRWS) compared with conventional SAR. Moving target indication (MTI) is an important application of spaceborne HRWS SAR systems. In contrast to previous studies of SAR MTI, the HRWS SAR mainly faces the problem of under-sampled data of each channel, causing single-channel imaging and processing to be infeasible. In this study, the estimation of velocity is equivalent to the estimation of the cone angle according to their relationship. The maximum likelihood (ML) based algorithm is proposed to estimate the radial velocity in the existence of Doppler ambiguities. After that, the signal reconstruction and compensation for the phase offset caused by radial velocity are processed for a moving target. Finally, the traditional imaging algorithm is applied to obtain a focused moving target image. Experiments are conducted to evaluate the accuracy and effectiveness of the estimator under different signal-to-noise ratios (SNR). Furthermore, the performance is analyzed with respect to the motion ship that experiences interference due to different distributions of sea clutter. The results verify that the proposed algorithm is accurate and efficient with low computational complexity. This paper aims at providing a solution to the velocity estimation problem in the future HRWS SAR systems with multiple receive channels.

MuLoG, or How to Apply Gaussian Denoisers to Multi-Channel SAR Speckle Reduction?

Speckle reduction is a longstanding topic in synthetic aperture radar (SAR) imaging. Since most current and planned SAR imaging satellites operate in polarimetric, interferometric, or tomographic modes, SAR images are multi-channel and speckle reduction techniques must jointly process all channels to recover polarimetric and interferometric information. The distinctive nature of SAR signal (complex-valued, corrupted by multiplicative fluctuations) calls for the development of specialized methods for speckle reduction. Image denoising is a very active topic in image processing with a wide variety of approaches and many denoising algorithms available, almost always designed for additive Gaussian noise suppression. This paper proposes a general scheme, called MuLoG (MUlti-channel LOgarithm with Gaussian denoising), to include such Gaussian denoisers within a multi-channel SAR speckle reduction technique. A new family of speckle reduction algorithms can thus be obtained, benefiting from the ongoing progress in Gaussian denoising, and offering several speckle reduction results often displaying method-specific artifacts that can be dismissed by comparison between results.

Improved Signal Reconstruction Algorithm for Multichannel SAR Based on the Doppler Spectrum Estimation

For high-resolution wide-swath synthetic aperture radar imaging algorithms, signal reconstruction is a key step. The steering vector plays an important role in signal reconstruction, which can be constructed by the ambiguity components. The information of the ambiguity components, e.g., number and index, is usually regarded to be constant and known. However, we find that the information of ambiguity components is always a piecewise function of the baseband frequency. This means that the steering vector cannot be preconstructed accurately and it will negatively affect the signal reconstruction. This paper presents an improved signal reconstruction method based on the Doppler spectrum estimation. The proposed method can estimate the variant ambiguity components to form the steering vector exactly by the Capon estimation. As a result, the method is able to restore the Doppler spectrum entirely and performs well on the noise reduction. Moreover, the baseband Doppler centroid and antenna pattern can be obtained in the proposed method. Simulated data and airborne raw data are processed to validate the algorithm.

Image-Based Target Detection and Radial Velocity Estimation Methods for Multichannel SAR-GMTI

In order to enhance the performance of spaceborne synthetic aperture radar–ground moving target indication (SAR-GMTI) systems, multichannel systems with large and preferably nonuniform baselines are required. In this paper, SAR-GMTI algorithms for multichannel SAR systems, which we call multichannel displaced phase center antenna (DPCA), multichannel along track interferometry (ATI), and multichannel DPCA-ATI, are presented. Multichannel DPCA is a deterministic algorithm for clutter and azimuth ambiguity suppression. It successfully suppresses not only uniform azimuth ambiguities but also nonuniform isolated ones, since it does not require uniform clutter covariance assumption as adaptive algorithms do. Multichannel ATI and multichannel DPCA-ATI are the algorithms for target radial velocity estimation. Both of them reduce the target radial velocity ambiguities, which arise with the long baseline systems, by exploiting the multiple receive channel signals. And multichannel DPCA-ATI further achieves robust performance to clutter influence by suppressing the clutter and the azimuth ambiguity in advance. The performances of the proposed algorithms are shown through airborne Ku-band three-channel SAR experiments. It is shown that the multichannel DPCA suppresses strong azimuth ambiguity up to more than 20 dB, and the accuracy of the radial velocity estimation of the multichannel DPCA-ATI is on the order of 0.1 m/s. Furthermore, statistical performance analysis is presented to discuss the potential performance on the spaceborne system.

Multichannel and Wide-Angle SAR Imaging Based on Compressed Sensing.

The multichannel or wide-angle imaging performance of synthetic aperture radar (SAR) can be improved by applying the compressed sensing (CS) theory to each channel or sub-aperture image formation independently. However, this not only neglects the complementary information between signals of each channel or sub-aperture, but also may lead to failure in guaranteeing the consistency of the position of a scatterer in different channel or sub-aperture images which will make the extraction of some scattering information become difficult. By exploiting the joint sparsity of the signal ensemble, this paper proposes a novel CS-based method for joint sparse recovery of all channel or sub-aperture images. Solving the joint sparse recovery problem with a modified orthogonal matching pursuit algorithm, the recovery precision of scatterers is effectively improved and the scattering information is also preserved during the image formation process. Finally, the simulation and real data is used for verifying the effectiveness of the proposed method. Compared with single channel or sub-aperture independent CS processing, the proposed method can not only obtain better imaging performance with fewer measurements, but also preserve more valuable scattering information for target recognition.

다채널 영상레이다를 위한 다중대역 송수신기 개발

In this paper, we designed and fabricated the multi band Transceiver Assembly(TCA) for the Multi Channel Synthetic Aperture Radar(MCSAR) containing C-band, X-band, Ku-band and we researched to verify electrical performance of TCA. The transceiver consists of transmitters, receivers, signal selection modules for each band, and stability oscillator, frequency synthesizer, controller, power distributor. The transceiver has a receive path selection and bandwidth selection functions in accordance with the operating mode. And the transceiver can transmit and receive all three bands simultaneously, each band has a bandwidth of up to 300 MHz. Final transmission output of transceiver for each band is over 20 dBm to be suitable for driving the T/R module. Receiver bandwidth is selected according to the required function and receiver gain has approximately C-band 52 dB, X-band 50 dB, Ku-band 60 dB, the maximum noise figure of Ku-band V polarization is 4.28 dB in the whole band H, V polarization. As a result of the electrical performance test, a multi-band TCA is satisfied the property requirements of the MCSAR.

Modified Multichannel Reconstruction Method of SAR With Highly Nonuniform Spatial Sampling

The traditional filter bank algorithm (FBA) for a multichannel synthetic aperture radar (SAR) system can provide an unambiguous recovery. However, the FBA may result in a seriously signal-to-noise ratio (SNR) loss or might even fail to reconstruct the spectrum if there is highly nonuniform sampling in azimuth. It is the general case because pulse repetition frequency (PRF) cannot be selected flexibly for spaceborne imaging system. In this paper, a new algorithm for processing highly nonuniform sampled SAR data to improve the SNR is presented. The proposed method is based on the operation of ambiguity-index screening (AIS) and the minimum mean square error (MMSE) criterion. It can be utilized to reconstruct the spectrum even in the presence of highly nonuniform sampling or coinciding sampling. The approach can significantly improve the SNR especially for the highly nonuniform sampling, and the azimuth ambiguity-to-signal ratio obtained by the proposed method is superior to the traditional one for a wide range of PRF. The proposed algorithm is validated by the simulated data and the real two-channel radar raw data acquired by C-band airborne SAR system with a bandwidth of 210 MHz, which is designed by the Department of Space Microwave Remote Sensing System, Institute of Electronics, Chinese Academy of Sciences.

Maritime Signature Correction With the NRL Multichannel SAR

This paper describes the Naval Research Laboratory Multichannel Synthetic Aperture Radar (NRL MSAR) and presents initial results from the first field deployment of this system. The NRL MSAR is an airborne test bed designed to investigate remote sensing and surveillance applications that exploit multiple along-track phase centers, particularly applications that require measurement of scene motion. The system operates at X-band and supports 32 along-track phase centers through the use of two transmit horns and 16 receive antennas. As illustrated in this paper, SAR images generated with these phase centers can be coherently combined to directly measure scene motion using the velocity SAR algorithm, and these measurements can then be used to correct the image distortion that the motion causes. In September 2014, this unique radar was deployed for the first time on an airborne platform. This paper presents a description of the system and results from its inaugural deployment, including the correction of distorted maritime signatures. These data were collected over an ocean inlet and contain a variety of moving backscatter sources, including automobiles, ships, shoaling ocean waves, and tidal currents.

Phase bias estimation for multi‐channel HRWS SAR based on Doppler spectrum optimisation

By applying digital beam-forming (DBF) technique, the along-track multi-channel synthetic aperture radar (SAR) system can simultaneously achieve high-resolution and wide-swath (HRWS) imaging. However, the presence of unavoidable phase biases tends to degrade the DBF performance. To address this issue, a novel phase bias estimation algorithm based on Doppler spectrum optimisation is proposed. By exploiting the fact that phase bias would cause Doppler spectrum broadened, the phase biases can be successfully estimated by maximising a sharpness optimisation of the Doppler spectrum. The effectiveness of the algorithm is validated by experimental result carried out on the SAR data collected by an air-borne multi-channel system.

Image reconstruction method for stepped-frequency multichannel bistatic SAR

ABSTRACTSingle-input multiple-output and multiple-input multiple-output configurations for stepped-frequency bistatic SAR (BiSAR) are proposed in this article to deal with the contradiction between Doppler ambiguity and swath width that arises in the stepped-frequency single-channel BiSAR. In the two new configurations, the space variance of range error within a pulse cluster becomes more prominent. This feature requires more precise range error compensation to maintain high-quality imaging. For this problem, a synthetic bandwidth method embedded in back projection algorithm is proposed. The simulation results validate the effectiveness of the two configurations and the image reconstruction method.

Modified reconstruction algorithm based on space-time adaptive processing for multichannel synthetic aperture radar systems in azimuth

A spectrum reconstruction algorithm based on space–time adaptive processing (STAP) can effectively suppress azimuth ambiguity for multichannel synthetic aperture radar (SAR) systems in azimuth. However, the traditional STAP-based reconstruction approach has to estimate the covariance matrix and calculate matrix inversion (MI) for each Doppler frequency bin, which will result in a very large computational load. In addition, the traditional STAP-based approach has to know the exact platform velocity, pulse repetition frequency, and array configuration. Errors involving these parameters will significantly degrade the performance of ambiguity suppression. A modified STAP-based approach to solve these problems is presented. The traditional array steering vectors and corresponding covariance matrices are Doppler-variant in the range-Doppler domain. After preprocessing by a proposed phase compensation method, they would be independent of Doppler bins. Therefore, the modified STAP-based approach needs to estimate the covariance matrix and calculate MI only once. The computation load could be greatly reduced. Moreover, by combining the reconstruction method and a proposed adaptive parameter estimation method, the modified method is able to successfully achieve multichannel SAR signal reconstruction and suppress azimuth ambiguity without knowing the above parameters. Theoretical analysis and experiments showed the simplicity and efficiency of the proposed methods.

Clutter-Cancellation-Based Channel Phase Bias Estimation Algorithm for Spaceborne Multichannel High-Resolution and Wide-Swath SAR

When combined with digital beam-forming (DBF) techniques, multichannel synthetic aperture radar (SAR) systems can achieve high-resolution and wide-swath SAR imaging. However, inevitable channel biases will degrade the performance of DBF in practice. To address this problem, a novel channel phase bias estimation algorithm is proposed in this letter. Theoretical analysis reveals that the signal of the first channel, which is considered as the reference channel, can be reconstructed from the signals of other channels, regardless of noise and signals outside the Doppler bandwidth. In the presence of phase biases, there is a reconstruction error after the cancellation by subtracting this reconstructed signal from the original signal. However, by minimizing the reconstruction error, the channel phase biases can be precisely estimated. The effectiveness of the proposed algorithm is validated by the experimental results.

Moving Target Detection via Efficient ATI-GoDec Approach for Multichannel SAR System

Clutter suppression and ground moving target indication (GMTI) are challenging tasks for multichannel synthetic aperture radar (MC-SAR) systems. In recent years, robust principal component analysis (RPCA), such as the augmented Lagrange multiplier method (ALM) and go decomposition (GoDec) algorithm, has drawn considerable attention for its excellent performance in distinguishing the different parts from a set of correlative database. In this letter, an efficient along-track interferometry GoDec (ATI-GoDec) approach is proposed for GMTI in MC-SAR systems under a strong clutter background. The proposed method can be separated into two sections: the predetection and the postdetection. The predetection by an efficient ATI RPCA method can decrease missing targets, and postdetection with a novel magnitude and phase (M&P) detection has the ability to reduce the false targets. As a result, the proposed method can provide a more robust performance by a comparison to the traditional ATI detection. It can also widen the tolerant values of the preset cardinality and decrease the probability of false alarm compared with the conventional GoDec algorithm. Moreover, the proposed method only takes several iterations to reach the convergence by solving the optimization problem of the RPCA model, which makes it more efficient than the previous RPCA methods. The results by applying the proposed method into a set of real SAR data are consistent with the analysis presented in this letter.