SIGNAL MODELING FOR AIRBORNE HIGH-RESOLUTION MULTICHANNEL CSSAR-GMTI SYSTEMS

This paper deals with the issue of ground moving target imaging and motion parameter estimation with an airborne dual-channel circular stripmap synthetic aperture radar (CSSAR) system. Although several methods of ground moving target motion parameter estimation have been proposed for the conventional airborne linear stripmap SAR, they cannot be applied to airborne CSSAR because the range history of a ground moving target for airborne CSSAR is different than that for airborne linear stripmap SAR. In this paper, the moving target’s range history for airborne dual-channel CSSAR and the target signal model after the displaced phase center antenna processing are derived, and a new ground moving target imaging and motion parameter estimation algorithm is developed. In this algorithm, the estimation of baseband Doppler centroid and its compensation are first performed. Then focusing is implemented in the 2-D frequency domain via phase multiplication, and the target is focused in the SAR image without azimuth displacement due to the compensation of the Doppler shift caused by its motion. Finally, the target’s motion parameters are estimated with its Doppler parameters and its position in the SAR image. Numerical simulations are conducted to validate the derived range history and the performance of the proposed algorithm.

Moving targets localization is an important challenge in current synthetic aperture radar (SAR) — ground moving target indication (GMTI) system. The along track interferometry (ATI) method is usually used for GMTI in SAR, however, which suffers from ambiguous parameters estimation due to wrapped phase and less robust to estimation errors (of system parameters and motion parameters of the moving targets). Focusing on these, we propose a new neural network based method to improve the moving targets localization performance. After analyzing the main error source of the conventional ATI method, we utilize an error back propagation (BP) neural network to replace the processing after range compression in the ATI method. And the proposed method is proved effective by the experiments, and it performs much better than the conventional ATI method in localization accuracy, efficiency and robustness.

In this paper, we propose the two-dimensional imaging response of three-dimensional moving target via synthetic aperture radar (SAR) with back-projection imaging algorithm. Firstly, we analyzed the imaging response for each single echo, which is the intersection of Doppler isodop and iso-range contour. Then, we come up with a focus condition for moving target SAR imaging. Besides, we find that the Doppler frequency will cause a shift and the motion trail of moving target will draw a curve in the imaging result over synthetic aperture time. Meanwhile, we provide the numerical simulation experiments of moving point targets via linear SAR and circular SAR with X-band and THz-band, respectively, to verify the conclusion of moving target imaging response.

Moving target brings out the different position shifts and defocusing across the image sequences acquired by circular synthetic aperture radar (CSAR) due to the Doppler shift and range smear effects. In this paper, a novel moving target detection approach for single-channel CSAR is proposed based on deep neural network (DNN). A dual-channel densely connected convolutional network (DenseNet) in consideration of complex-valued information is exploited for distinguishing the ground clutter and moving target. In terms of limited CSAR measure data set available for training the DNN network, simulated moving target samples are generated and fused into the measured ones under the various motion parameters. Finally, experiments have demonstrated that the proposed DenseNet for single-channel CSAR system processes an accepted detection performance and effectively overcomes the insufficiency of the limited dataset applications.

This paper proposes a new ground moving target imaging algorithm for high-resolution airborne circular stripmap synthetic aperture radar (CSSAR)-ground moving target indication (GMTI) systems. In the proposed algorithm, the range cell migration correction is performed in the 2D frequency domain via a phase multiplication. The azimuth compression is performed in the range Doppler domain. A key step of the proposed algorithm is to utilize an iterative strategy to achieve an accurate correction of the range cell migration. This step makes the proposed algorithm work well for high-resolution CSSAR-GMTI systems. Numerical simulations are conducted to validate the proposed algorithm.

The sequence of echoes detected by an active Synthetic Aperture Sonar (SAS) is coherently added in an appropriate way to produce an image with greatly enhanced resolution in the azimuth, or along-track direction when compared with an image obtained from a standard Side Looking Sonar (SLS). The SAS processing originates from the Synthetic Aperture Radar (SAR) concept. A complete introduction to SAR technique can be found in (Sherwin et al., 1962), (Walker, 1980), (Wiley, 1985) and (Curlander & McDonough, 1991). Raytheon was issued in 1969 a patent for a high-resolution seafloor imaging SAS (Walsh, 1969) and 1971 analyzed a potential system in terms of its resolution and signal-to-noise ratio. Cutrona was the first well-known radar specialist to point out how the various aspects of SAR could be translated to an underwater SAS (Cutrona, 1975). Hughes (1977) compared the performance of a standard SLS to an SAS and showed that the potential mapping rate for SAS was significantly higher than for side-looking sonar. At the time there was an assumption that the instability of the oceanic environment would prevent the formation of SAS imagery. Experimental work, which was performed by Williams (1976) and Christoff et al. (1982), refuted the instability worry. The verification of this assertion performed at higher frequencies by Gough & Hawkins (1989). Later, other concerns regarding the stability of the towed platform were also raised and some railor wire-guided trails where set up to avoid this extra complication. Nowadays there are a multiple of systems as hull mounted SAS systems, towed SAS systems and Autonomous Underwater Vehicles (AUV) systems. For further reading one can find an extended historical background of SAS in (Gough & Hawkins, 1997). Time and experience were needed to adapt SAR algorithms to SAS systems; the SAS systems use smaller radiating elements in proportion to the wavelength, which leads to higher radiation pattern of SAS with respect to SAR. The range migration effect on synthetic aperture processing is significant and pronounced in SAS imagery. An additional difference between SAR and SAS systems is the synthetic aperture time being greater in one order of magnitude in SAS, which leads to a phase corruption due to the medium fluctuations and platform instabilities. Typical synthetic aperture times for SAR are of the order of seconds with a medium coherence of some days, whereas for SAS the typical synthetic aperture time is of the order of several minutes with a similar medium coherence time (Marx et al. 2000). O pe n A cc es s D at ab as e w w w .in te ch w eb .o rg

In this paper, we present the results of a modeling study to examine the interference effect of microDopplers caused by offshore wind farms on airborne sensors operating in the synthetic aperture radar (SAR) and ground moving target indicator (GMTI) modes. The modeling is carried out by generating CAD instantiations of the dynamic wind turbine and using the high-frequency electromagnetic code Xpatch to perform the scattering calculations. Artifacts in the resulting SAR and GMTI signatures are evaluated for interference with tracking of boats in coastal waters. Results of signal filtering algorithms to reduce the dynamic turbine clutter in both SAR images and GMTI displays are presented.

Displaced phase center array (DPCA) and along-track interferometry (ATI) have been widely used for ground moving target indication (GMTI) in multi-channel circular synthetic aperture radar (CSAR) system. In ideal conditions, these methods can suppress background clutter effectively. However, the nonideal movement of platform may create a nonzero crab angle, which will induce a cross-track baseline offset and affect GMTI processing seriously. This letter analyzes the influence of crab angle on interferometric phase theoretically. Here, we propose a two-step phase calibration method to greatly improve the performance of CSAR-GMTI by eliminating the range-varying phase error. This method is independent of imaging and GMTI processing. Simulated and measured data results verify the correctness of the theoretical analysis and the validity of the proposed method.

Array synthetic aperture radar (SAR) is one of the hot areas in radar imaging field because of its three-dimensional (3-D) imaging ability. Combining the advantages of linear array SAR in aspect of side-lobe suppression and circular SAR in aspect of high resolution, a new kind of annular array synthetic aperture radar (AASAR) mode is employed for 3-D microwave imaging. Based on the mathematical derivation of AASAR model, the sparse layout of the annular array in the cross-track direction can acquire 3-D high resolution and effective side-lobe suppression ability. Then on this basis, a proto-type AASAR experiment system is built, and some 3-D AASAR imaging outdoor experiments are conducted. Through the experiment result, the validity of 3-D AASAR imaging can be demonstrated.

The use of spaceborne synthetic aperture radar (SAR) for ground moving target indication (GMTI) has recently attracted a great deal of interest. In this study, an efficient imaging algorithm for spaceborne SAR/GMTI systems is proposed. The proposed imaging algorithm first implements the secondary range compression and the range cell migration correction in the two‐dimensional frequency domain and then the azimuth compression in the range Doppler domain. The proposed algorithm can finely focus the stationary scene and coarsely focus multiple slow‐moving targets simultaneously without a priori knowledge of targets’ motion parameters and position parameters. Moreover, the proposed algorithm is interpolation free and can be efficiently implemented by using only complex multiplications and fast Fourier transforms. These advantages make the proposed algorithm useful in practice. Experimental results from both simulated data and real data validate the proposed algorithm.

In circular synthetic aperture radar (CSAR), radar collects data over a circular trajectory. This wide-angle non-linear collection geometry makes CSAR capable of obtaining both two-dimensional (2D) high resolution image and three-dimensional (3D) image. In this paper, compressive sensing technique is used in 3D CSAR imaging. Not only echo samples used in imaging are greatly reduced, but also the imaging results are with good performance. However, the consumed time of reconstruction is very long. In order to overcome this problem, graphic process unit (GPU) is furtherly used in 3D compressive sensing CSAR imaging in this paper. Simulation results show that GPU can improve the efficiency of the 3D reconstruction.

Ground moving target indication (GMTI) plays an important role in surveillance and reconnaissance applications, but it is a difficult problem due to the impacts of stationary clutter. This paper proposes a multichannel synthetic aperture radar (SAR) using waveform diversity, namely, multiple-input multiple-output (MIMO) SAR and distinct carrier frequency for GMTI applications. The proposed approach employs MIMO configuration with multiple antennas in azimuth and orthogonal waveform diversity. In doing so, multiple independent transmit-receive channels are formulated at the receiver. Since each antenna uses both waveform diversity and distinct carrier frequency, after clutter cancellation and noise suppression by the displaced phase center antenna (DPCA) and along-track interferometry (ATI) combined processing algorithm, the cross-track velocity is estimated through double-interferometry processing. Next, the Doppler parameters of moving targets are estimated with the fractional Fourier transform algorithm and then GMTI is obtained by a joint signal processing algorithm. Finally, the moving targets are focused with a general chirp scaling imaging algorithm. All the proposed methods are verified by simulation results.

We present a new method for estimating the motion parameters of a target from its inverse synthetic aperture radar (ISAR) signature. This method uses the phase of the target's echo transfer function to calculate a focal quality indicator while avoiding two-dimensional Fourier processing. The focal quality indicator reaches the global minimum of a parametric motion surface when the phase is compensated with the target's actual motion parameters. The presence of an absolute minimum without local minima guarantees that the estimated motion parameters are an accurate representation of the target's motion and allows the use of a simple search procedure. Polynomial fitting is incorporated to the new method to improve the robustness by reducing estimation errors due to the finite order of the parametric motion model.

Inverse synthetic aperture radar (ISAR) imaging is one of the important high- resolution radar applications for moving target detection and identification. The radial velocity, radial acceleration, and acceleration rate of maneuvering targets can cause range cell migration and Doppler variation in the received signals, which will degrade the imaging quality. Therefore, these parameters should be estimated and compensated before imaging. In low signal-to-noise ratio (SNR) conditions, the conventional motion parameter estimation and compensation algorithms for maneuvering targets do not work properly. To effectively detect and identify the maneuvering targets in low SNR conditions, a new radar imaging algorithm is proposed. The major contributions are as follows: 1) a novel algorithm for envelope migration correction is proposed with adjacent cross correlation function; 2) the target's motion parameters are estimated with the operations of Keystone transform and time-frequency transform to the adjacent cross correlation; 3) a theoretical analysis of the impact of motion parameters on the envelope migration is made, then cross-range phase estimation with the adjacent cross function is presented; 4) based on the estimated motion parameters of targets, a new algorithm for high-resolution ISAR imaging is developed.

This letter addresses an efficient algorithm for ground moving target detection and estimation of motion parameters by synthetic aperture radar (SAR). The proposed method outperforms the conventional robust principal component analysis (RPCA)–based ground moving target indication (GMTI) methods that were proposed in the literature. The ability to estimate the radial and along-track velocities of ground moving targets is provided. The rank constraint in the conventional RPCA problem will be automatically relaxed by employing a dictionary matrix for clutter representation. Thus, the new optimization problem will be solved easier with lower degrees of freedom. Furthermore, this dictionary helps to suppress the clutter of higher Doppler frequencies in case of wind blowing scenarios and intrinsic clutter motion modeling. By employing another dictionary matrix for all possible moving targets with different location and velocity, each solution of the optimization problem will be reasonable as it corresponds to a moving target. Although, the two dictionary matrices impose extra computational burden, this load will be prepared prior to other GMTI processing by the information of the SAR system and scenario parameters. Moreover, the algorithm is proposed for the single-channel SAR configurations and has lower computational load than the conventional RPCA-GMTI methods that have to process the recorded data of multichannel systems. Numerical and experimental results are used to evaluate the performance of the proposed method and validate the theoretical discussions.