Azimuth Ambiguity Research Articles

Unambiguous Signal Reconstruction Approach for SAR Imaging Using Frequency Diverse Array

The conflict between range and azimuth ambiguities is a challenging problem for spaceborne high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) imaging. In this letter, a novel ambiguity resolution approach based on frequency diverse array (FDA) is proposed to retrieve unambiguous signal from that with ambiguities in both range and azimuth domains. By exploiting the range-angle-dependent property of transmit steering vector in FDA and applying the second range dependence compensation approach, echoes from different ambiguous regions are separable in transmit spatial-Doppler frequency domains. Then a corresponding transmit beamformer is designed to extract spectrum component of each ambiguous region, which can be rearranged to comprise the desired unambiguous signal. Compatible with most existing azimuth ambiguity suppression algorithms which employ the receive degrees of freedom, the proposed approach can further enhance the capability of resolving ambiguity for HRWS SAR systems, and its effectiveness is verified by simulation experiments.

Azimuth Ambiguities Removal in Littoral Zones Based on Multi-Temporal SAR Images

Synthetic aperture radar (SAR) is one of the most important techniques for ocean monitoring. Azimuth ambiguities are a real problem in SAR images today, which can cause performance degradation in SAR ocean applications. In particular, littoral zones can be strongly affected by land-based sources, whereas they are usually regions of interest (ROI). Given the presence of complexity and diversity in littoral zones, azimuth ambiguities removal is a tough problem. As SAR sensors can have a repeat cycle, multi-temporal SAR images provide new insight into this problem. A method for azimuth ambiguities removal in littoral zones based on multi-temporal SAR images is proposed in this paper. The proposed processing chain includes co-registration, local correlation, binarization, masking, and restoration steps. It is designed to remove azimuth ambiguities caused by fixed land-based sources. The idea underlying the proposed method is that sea surface is dynamic, whereas azimuth ambiguities caused by land-based sources are constant. Thus, the temporal consistence of azimuth ambiguities is higher than sea clutter. It opens up the possibilities to use multi-temporal SAR data to remove azimuth ambiguities. The design of the method and the experimental procedure are based on images from the Sentinel data hub of Europe Space Agency (ESA). Both Interferometric Wide Swath (IW) and Stripmap (SM) mode images are taken into account to validate the proposed method. This paper also presents two RGB composition methods for better azimuth ambiguities visualization. Experimental results show that the proposed method can remove azimuth ambiguities in littoral zones effectively.

Maritime Surveillance With Undersampled SAR

According to the minimum antenna area constraint, synthetic aperture radar (SAR) systems require a low-pulse repetition frequency (PRF) to image the wide swaths in ocean surface monitoring scenarios. However, the low PRF that is lower than the Doppler bandwidth will cause azimuth ambiguities. This letter proposes a novel method of mitigating azimuth ambiguities when using an undersampled SAR system for ship detection over the open sea. In this letter, the concept of range subspectra is adopted to misregister the azimuth ambiguity signals. In addition, a change detection method that uses a principal component analysis and $k$ -means clustering is adopted to detect differences in the azimuth ambiguities between two range subspectra images in which the azimuth ambiguities are misregistered. By compensating for the ambiguities in the corresponding image, the ambiguities can be mitigated. This method is only appropriate for bright targets over dark backgrounds in which residual energy loss occurs for useful signals. Both simulated and real data processing results have validated the effectiveness of the proposed method and show that it is feasible for maritime surveillance.

Azimuth-Variant Phase Error Calibration Technique for Multichannel SAR Systems

Multiple azimuth channels are usually employed to overcome the inherent limitation between high resolution and wide swath in synthetic aperture radar systems. However, unavoidable channel phase errors will significantly degrade the performance of ambiguity suppression. Conventional calibration methods usually regard these phase errors as constants during the whole observation time and ignore the azimuth-variant phase errors, which may not totally suppress azimuth ambiguities especially for very strong targets. This letter presents an azimuth-variant phase error calibration technique. The proposed technique first selects a strong point-like target as the calibration source. Then, the azimuth-variant phase errors can be estimated by comparing the phase of the calibration source and the corresponding steering vector in the range-compressed signals. Besides, a preprocessing method is presented to improve the calibration accuracy when the selected calibration source is affected by noise or interferences. Theoretical analysis and experiments demonstrate the feasibility of the proposed technique.

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 Vessel Detection in Gaofen-3 SAR Images with Ultrafine Strip-Map Mode.

This study aims to detect vessels with lengths ranging from about 70 to 300 m, in Gaofen-3 (GF-3) SAR images with ultrafine strip-map (UFS) mode as fast as possible. Based on the analysis of the characteristics of vessels in GF-3 SAR imagery, an effective vessel detection method is proposed in this paper. Firstly, the iterative constant false alarm rate (CFAR) method is employed to detect the potential ship pixels. Secondly, the mean-shift operation is applied on each potential ship pixel to identify the candidate target region. During the mean-shift process, we maintain a selection matrix recording which pixels can be taken, and these pixels are called as the valid points of the candidate target. The norm regression is used to extract the principal axis and detect the valid points. Finally, two kinds of false alarms, the bright line and the azimuth ambiguity, are removed by comparing the valid area of the candidate target with a pre-defined value and computing the displacement between the true target and the corresponding replicas respectively. Experimental results on three GF-3 SAR images with UFS mode demonstrate the effectiveness and efficiency of the proposed method.

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.

PolSAR Ship Detection Based on the Polarimetric Covariance Difference Matrix

Ship detection using Polarimetric SAR data has attracted a lot of attention in recent years. Due to the sampling of the Doppler spectrum at finite intervals of the pulse repetition frequency, the azimuth ambiguities often appear in PolSAR images, which make the ship detection in PolSAR images frequently generating false alarms, especially in the case of low backscattering sea environment. In order to handle the problem and improve the performance of ship detection in PolSAR images, this paper presents a new method, which is mainly based on concentrating the polarimetric difference between ship pixels and background pixels. We first calculate a polarimetric covariance difference matrix, denoted as polarimetric covariance difference matrix (PCDM), by accumulating the elemental difference between the polarimetric covariance matrix at each pixel and the counterparts in its 3 × 3 neighbors. The SPAN detector is then applied on PCDM to obtain a coarse detection result. Meanwhile, we decompose the PCDM matrix to calculate a new polarimetric signature, called pedestal ship height (PSH), and use it together with the coarse detection result to distinguish ships from ambiguities. Extensive experiments on three real PolSAR datasets are carried out to demonstrate the effectiveness of the proposed method in comparing with other algorithms. The experimental results show that the proposed method not only detects ships effectively, but also can remove the azimuth ambiguities and reduce the false alarms significantly.

Depth Sensing Using Geometrically Constrained Polarization Normals

Analyzing the polarimetric properties of reflected light is a potential source of shape information. However, it is well-known that polarimetric information contains fundamental shape ambiguities, leading to an underconstrained problem of recovering 3D geometry. To address this problem, we use additional geometric information, from coarse depth maps, to constrain the shape information from polarization cues. Our main contribution is a framework that combines surface normals from polarization (hereafter polarization normals) with an aligned depth map. The additional geometric constraints are used to mitigate physics-based artifacts, such as azimuthal ambiguity, refractive distortion and fronto-parallel signal degradation. We believe our work may have practical implications for optical engineering, demonstrating a new option for state-of-the-art 3D reconstruction.

New Insights Into Ambiguities in Quad-Pol SAR

Quadrature-polarimetric (quad-pol) synthetic aperture radar (SAR) is a well-established technique which has numerous applications in remote sensing. However, spaceborne quad-pol SAR systems are often constrained by severe range and azimuth ambiguities. A deep understanding of the nature of ambiguities in conventional, hybrid, and $\pm \pi $ /4 quad-pol SAR allows a correct evaluation of the ambiguity-to-signal ratio and the design of systems optimized for ambiguity suppression. In that respect azimuth phase coding and merging data available from both cross-polarized channels play an important role. The results of this paper are relevant not only for the design of future spaceborne quad-pol SAR systems, including staggered SAR ones, but also for the optimal exploitation of quad-pol SAR systems currently in operation.

Signal Processing for a Multiple-Input, Multiple-Output (MIMO) Video Synthetic Aperture Radar (SAR) with Beat Frequency Division Frequency-Modulated Continuous Wave (FMCW)

In this paper, we present a novel signal processing method for video synthetic aperture radar (ViSAR) systems, which are suitable for operation in unmanned aerial vehicle (UAV) environments. The technique improves aspects of the system’s performance, such as the frame rate and image size of the synthetic aperture radar (SAR) video. The new ViSAR system is based on a frequency-modulated continuous wave (FMCW) SAR structure that is combined with multiple-input multiple-output (MIMO) technology, and multi-channel azimuth processing techniques. FMCW technology is advantageous for use in low cost, small size, and lightweight systems, like small UAVs. MIMO technology is utilized for increasing the equivalent number of receiving channels in the azimuthal direction, and reducing aperture size. This effective increase is achieved using a co-array concept by means of beat frequency division (BFD) FMCW. A multi-channel azimuth processing technique is used for improving the frame rate and image size of SAR video, by suppressing the azimuth ambiguities in the receiving channels. This paper also provides analyses of the frame rate and image size of SAR video of ViSAR systems. The performance of the proposed system is evaluated using an exemplary system. The results of analyses are presented, and their validity is verified using numerical simulations.

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.

Array error estimation method for multichannel synthetic aperture radar systems in azimuth

Multichannel synthetic aperture radar systems are usually employed to suppress azimuth ambiguity and realize high-resolution wide-swath imaging. However, unavoidable array errors will significantly degrade the performance of ambiguity suppression and imaging quality. This paper presents an array error estimation method based on cross correlation. First, unambiguous Doppler spectra are obtained by selecting a short length of range profiles from strong targets. Then, array errors are estimated by a proposed cross-correlation method. Finally, a preprocessing method to improve the estimation accuracy is proposed. The proposed method takes full advantage of the training samples from strong targets and estimates array errors by the coherent integration technique, which improves the estimation accuracy and robustness. Theoretical analysis and experiments based on simulations and measurements showed the validity of the proposed method, especially in low signal-to-noise ratios.

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.

Doppler Spectrum-Based NRCS Estimation Method for Low-Scattering Areas in Ocean SAR Images

The image intensities of low-backscattering areas in synthetic aperture radar (SAR) images are often seriously contaminated by the system noise floor and azimuthal ambiguity signal from adjacent high-backscattering areas. Hence, the image intensity of low-backscattering areas does not correctly reflect the backscattering intensity, which causes confusion in subsequent image processing or interpretation. In this paper, a method is proposed to estimate the normalized radar cross-section (NRCS) of low-backscattering area by utilizing the differences between noise, azimuthal ambiguity, and signal in the Doppler frequency domain of single-look SAR images; the aim is to eliminate the effect of system noise and azimuthal ambiguity. Analysis shows that, for a spaceborne SAR with a noise equivalent sigma zero (NESZ) of −25 dB and a single-look pixel of 8 m × 5 m, the NRCS-estimation precision of this method can reach −38 dB at a resolution of 96 m × 100 m. Three examples are given to validate the advantages of this method in estimating the low NRCS and the filtering of the azimuthal ambiguity.

Accurate Reconstruction and Suppression for Azimuth Ambiguities in Spaceborne Stripmap SAR Images

In this letter, an accurate mathematical model for azimuth ambiguity in stripmap synthetic aperture radar (SAR) images is first constructed, with an azimuth ambiguity factor (AAF) defined as the residual amplitude and phase terms of ambiguities. Next, a novel framework for reconstructing and suppressing azimuth ambiguity is proposed based on the analysis of the AAF. In this framework, azimuth ambiguities are accurately reconstructed by applying reconstruction filters in the range Doppler and 2-D frequency domain, and then, the reconstructed signal is used for suppressing azimuth ambiguities. Moreover, the proposed framework does not depend on the statistical characteristics of a SAR image and is capable of reducing the space-variant ambiguities. As verified by both simulated data and real TerraSAR-X data, the proposed method is capable of suppressing azimuth ambiguities in SAR images.

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.

A Weighted Backprojection Algorithm for Azimuth Multichannel SAR Imaging

A backprojection algorithm (BPA), a time domain synthetic aperture radar (SAR) imaging algorithm, can be widely used without modification in various imaging modes, like stripmap, spotlight, sliding spotlight, etc. However, BPA also suffers when used in azimuth multichannel SAR due to the nonuniform sampling problem caused by a nonideal pulse repetition frequency. In this letter, we propose a weighted BPA (WBPA) for azimuth multichannel SAR imaging. Derived from the filter-bank-based reconstruction method, WBPA adds a weighting procedure to BPA. Simulations and an airborne SAR data experiment demonstrate that WBPA can perfectly suppress the azimuth ambiguities under band-limited circumstances. WBPA extends the applicable scope of BPA.

Onboard Processing for Data Volume Reduction in High-Resolution Wide-Swath SAR

High-resolution wide-swath synthetic aperture radar (SAR) systems are very attractive for the observation of dynamic processes on the Earth's surface, but they require the downlink of a huge volume of data. In order to comply with azimuth ambiguity requirements, in fact, a pulse repetition frequency much higher than the required processed Doppler bandwidth is often desirable. The volume of downlinked data, however, can be drastically reduced by performing Doppler filtering and decimation on board. A finite-impulse-response filter with a relatively small number of taps suffices to suppress the additional ambiguous components and to recover the original impulse response. This strategy is of special relevance for staggered SAR systems, which are typically characterized by a high oversampling factor. The proposed data reduction technique is also baseline for Tandem-L, where onboard Doppler filtering, resampling, and decimation will be jointly implemented.

L q regularisation‐based synthetic aperture radar image feature enhancement via iterative thresholding algorithm

A novel L q (0 < q ≤ 1) regularisation-based synthetic aperture radar (SAR) image feature enhancement method via SAR complex image data is presented. Compared with conventional L q regularisation-based compressive sensing imaging technique with full-sampling raw data, the proposed method can achieve the same effect of image feature enhancement while enjoying much less computational cost. Through simulations and experiments, the superiority of the proposed method is demonstrated in terms of sidelobe, azimuth ambiguity, clutter suppression and super-resolution.