Motion Compensation for Airborne SAR via Parametric Sparse Representation

Synthetic aperture radar (SAR) is a widely used remote sensing observation technique. However, SAR raw echo data may be lost during the process of data acquisition by radar platform. In this paper, the imaging problem of SAR echo signal with periodically missing data along the azimuth is analyzed and a novel imaging method is proposed. Firstly, the problem of artificial artifact targets caused by periodically missing data is explained in detail, and the corresponding mathematical model is established. Then, the recovery method based on the RELAX algorithm with periodic notches data is proposed. In addition, when the size of two-dimensional (2D) echo data are large, block restoration along the azimuth is proposed to reduce the amount of calculation. Finally, the advantages of the algorithm proposed in this paper is demonstrated by the points target simulated SAR echo data processing and the real raw SAR echo data processing. When the azimuth periodically missing data rate is 50%, the SAR echo data can be recovered and the well-focused image can be obtained. Comparing the image entropy value and structural similarity index (SSIM) of the focused image, it proves the superiority of the proposed algorithm in solving the imaging problem of SAR azimuth periodically missing data.

Coherent range-dependent map-drift algorithm for improving SAR motion compensation

Aperture-dependent motion compensation is important for wide beam Synthetic Aperture Radar (SAR) data processing. This paper studies a wide beam motion compensation algorithm based on frequency division. It takes blocks along azimuth dimension in frequency domain and applies angle-variant motion compensation in time domain. With this frequency division based motion compensation approach, the effects of aperture-dependent residual phase errors are corrected precisely. The rationale and procedure of this algorithm are introduced in detail. Point targets and images of a P-band airborne SAR with motion errors are simulated to validate this algorithm. Compared with the wide beam motion compensation algorithms based on time division, the proposed algorithm has better performance, especially in terms of high-frequency motion errors.

In the current complex electromagnetic environment, the imaging quality of synthetic aperture radar (SAR) may be severely degraded by wideband interference (WBI), which occupies a wide frequency band overlapping with the frequency band of the SAR system, leading to great difficulties in WBI suppression. To address this problem, we propose a method based on the masked second-order multisynchrosqueezing transform (MSST2) to effectively extract WBI from corrupted SAR data. First, the SAR echo is characterized in the time-frequency (TF) domain by the short-time Fourier transform (STFT) with adaptive window width, and a TF mask for the WBI is generated. Then, the energy of the WBI is concentrated with high resolution by MSST2, and the TF mask is refined according to the MSST2 result. Finally, the WBI is accurately reconstructed from the MSST2 result masked by the refined TF mask and is subtracted from the SAR echo. Abundant experimental results for measured SAR data with simulated and real WBI demonstrate the superior performance and practicability of the proposed method.

In unmanned aerial vehicle (UAV) synthetic aperture radar (SAR), step-frequency mode is usually used due to the limitation of size and weight. Due to the small size and weight, the trajectory deviation is so serious that the motion compensation becomes very complex. In order to estimate and compensate the motion error in UAV SAR, a two-step motion compensation approach is proposed in this paper. Firstly, the global positioning system (GPS) and inertial navigation system (INS) data is used for the coarse compensation to eliminate the major motion error. Secondly, fine phase error compensation based on raw SAR data is processed to circumvent the residual phase error. The fine phase error is estimated by weighted phase gradient autofocus (WPGA) in each sub-pulse of step-frequency mode. Then the weight least square (WLS) method is used to obtain the final focusing phase from the estimated phase of sub-pulse. Real data experiments show that the proposed method is suitable for UAV SAR motion compensation.

Synthetic Aperture Radar (SAR) echo simulation is an effective tool of the radar system design, which enables us to validate imaging algorithms and evaluate the performance of SAR systems before actual use. The increasing demand of higher SAR resolution makes the SAR simulation more and more complicated. The traditional simulation methods are not precise enough so that a new simulation method applicable to most complicated targets is needed. This paper demonstrates a novel simulation method based on the theory of electromagnetic scattering which simulates the received echo data through taking use of the backscattered electric field. Our simulation method can be used to simulate a complicated target in SAR simulation. This method opens a door to conducting SAR echo simulation with theory of signal and system and the electromagnetic scattering taken into consideration, though a few improvements are needed to increase the performance of the SAR simulation.

Airborne synthetic aperture radar (SAR) system is an essential tool for modern remote sensing applications. The aircraft is easily affected by the atmospheric turbulence, leading to deviations from the ideal track. To enable high-resolution imagery, a navigation system is usually mounted on the aircraft. Due to the limitation of the navigation system's accuracy, motion errors estimated from the SAR raw data are needed. In this paper, a novel motion compensation algorithm, which is based on the instrumental variables (IV) method, is proposed. We call this IV-based algorithm the IVA algorithm. In this algorithm, double-derivative motion errors are estimated without modeling the random disturbances to be a zero-mean Gaussian distribution and to be created from mutually independent noise, which makes it more robust and accurate in focusing SAR images. Before the motion error estimation, a Savitzky–Golay filter is performed to reduce the phase estimation errors, in which the phase is obtained by the phase gradient autofocus algorithm. Finally, the estimated motion errors are used to compensate the received signal with the range-dependent model. The IVA algorithm is validated by using real airborne SAR data, and experimental results show that the proposed algorithm achieve an excellent performance in airborne SAR systems.

Synthetic Aperture Radar (SAR) is generally considered as an all-time and all-weather system. However, weather conditions will sometimes still affect the SAR imaging, especially when rain rate or operating frequencies are increased. In this paper, the influence of rainfall attenuation in multi-band 3-D complex target SAR imaging is investigated. As SAR echo can be considered as scattering from the target illuminated by incident wave, physical optics (PO) method is used to compute the scattered data because of its good balance between efficiency and accuracy in high frequency band. Numerical results demonstrate the rain attenuation impact on SAR image, when the relationship between rain rate and precipitation attenuation in multi-frequency band are quantitative analyzed.

This paper proposes a novel motion compensation algorithm for wide beam Synthetic Aperture Radar (SAR) based on frequency division. It applies motion compensation in time domain and corrects both low- and high- frequency motion errors. The rationale and procedure of this algorithm are introduced in detail. Point scatterers of a P-band airborne SAR with different motion errors are tested to validate this algorithm. Compared with traditional narrow beam motion compensation and available wide beam compensation, the proposed algorithm has better performance.

When using motion compensation approaches based on the measurement of motion sensors, the residual uncompensated motion errors due to measurement instrument inaccuracies contribute to phase errors and hence degrade Synthetic Aperture Radar (SAR) images. This paper presents a model to compute the phase error caused by Inertial Measurement Unit (IMU) measurement inaccuracies. By analyzing SAR motion compensation method and the effect of lever arm, this model derives the contribution of each term of IMU inaccuracies towards the residual uncompensated motion errors and provides a method to calculate each order of the residual phase error. According to the model, computed results of the airborne X-band SAR system with POS AV510 accord closely with the actual image quality.

Clutter suppression plays an important role in a synthetic aperture radar (SAR) system. The conventional SAR imaging methods are useful for distinguishing the echo signal and noise, but cannot separate the target signal from background clutter. Inspired by the signal separation ability of morphological component analysis (MCA), a novel SAR imaging method based on MCA is proposed to suppress the strong background clutter. In the new model, the SAR echo is considered as a linear superposition of target signal, clutter signal, and noise. According to different characteristics of morphological components, clutter dictionary and target dictionary are constructed to sparsely represent the clutter component and target component, respectively. Then, the MCA method based on the sparse representation and morphological diversity of signals is employed to decompose the SAR echo into the target signal, clutter signal, and noise. Finally, the separated target signal is processed to obtain the ultimate SAR image. Experimental results from simulated and real SAR data are provided to demonstrate the effectiveness of the proposed method.

A frequency-domain transfer function for synthetic-aperture radar (SAR) processing is derived as a function of SAR aperture time, which may then be used to weight inertial sensor PSD. Methods of emulating autofocus are also discussed. This transfer function essentially transforms inertial sensor noise into equivalent SAR phase noise. The SAR phase-noise spectrum is then used to derive the individual radar parameters of equivalent quadratic phase error, peak side lobe ration, and integrated side lobe ratio. An example of a specification for motion-compensation sensors using the above transfer functions is presented. >

The United Kingdom Ministry of Defence is conducting a long range synthetic aperture radar (SAR) technology demonstrator programme (TDP) in support of their airborne stand-off radar programme. A major goal is to develop a high-resolution airborne SAR with both strip map and spotlight modes. To attain the image quality objectives of the project, it is essential that very accurate motion compensation be applied to the radar returns to reduce image degradation, caused by spurious antenna phase center motion, to acceptable levels. The SAR motion compensation system (SARMC) includes a master inertial navigation system located near the center of mass of the host aircraft and a slaved strapdown inertial measurement unit mounted on the back of the radar antenna, as well as Doppler velocity and barometric and radar altimeters. The performance of the SARMC has been evaluated both by analysis and computer simulation. These evaluations accounted for all major system error sources, including errors associated with sensors, transfer alignment, and computation, with the system operating in an environment of moderate atmospheric turbulence. Results from these evaluations are presented. >

Multistatic synthetic aperture radar (SAR) have achieved significant performance in the field of anti-jamming for its flexible configuration. Hence, its capacity of anti-jamming is very important in electronic warfare. In addition, it is difficult to remove the false targets caused by the deceptive jammer from SAR echoes. We propose a novel anti-deceptive jamming method for multistatic SAR in this paper which is able to locate the deceptive jammer and eliminate its influence. We first apply maximally stable extremal region (MSER) and European-distances-based method to detect the false targets. The position of the jammer can then be obtained by exploiting the position information of the false targets and the SAR transmitters/receivers. At last, beamforming is applied to achieve the anti-deceptive jamming. Experimental results demonstrate the effectiveness of our proposed method.

In synthetic aperture radar (SAR) imaging, generation of fine resolution imagery requires measurement and compensation for the relative translational and rotational motions between the antenna phase center (APC) and the scene being imaged. A difficulty arises when motion compensating stripmap mode signal history data from a SAR requiring a wide angle azimuth beamwidth. In general, the required compensation varies with scatterer location within the azimuth beam. The usual approach in stripmap motion compensation is to ignore this requirement and to compensate only the component of sensor motion in the nominal antenna boresight direction (usually broadside). In the widebeam system, this procedure can lead to unacceptable phase errors even if sensor motion is measured without error. In this paper, we survey the motion compensation challenge to ultra-wideband/widebeam (UWB/WB) SAR image formation. The emphasis here is on formation of fine resolution digital imagery from low frequency (VHF/UHF) UWB/WB data collected in stripmap mode by an airborne SAR system . We examine differences in motion compensation requirements and approaches between a UWB/WB system and a conventional X-band SAR system. This paper presents an improved motion compensation algorithm applicable to widebeam stripmap SAR. We demonstrate this procedure with imagery from the fine resolution ARPA/ERIM/NAWC P3 ultra-wideband radar system.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.