Baochang Liu

Bistatic SAR Data Focusing Using an Omega-K Algorithm Based on Method of Series Reversion

This paper deals with an omega-K algorithm for focusing bistatic synthetic aperture radar (SAR) data. The key of the proposed algorithm is the derivation of a frequency mapping function by using Neos method of series reversion. The registration of the focused image onto the ground plane is discussed in detail, which is based on a conclusion that the targets whose instantaneous Doppler frequencies at zero azimuth time are the same as that of the reference target at zero azimuth time will all be focused at the reference targets azimuth position in the focused image. The range invariance region size, which the proposed algorithm can process, is also determined in this paper. The proposed algorithm can handle extreme bistatic configurations with wide apertures and large squint angles. The effectiveness of the proposed algorithm is confirmed by simulation results. Although developed for the azimuth-invariant case, the proposed algorithm can be readily extended to the azimuth-variant case, as long as we divide the SAR data into blocks in the azimuth direction so that each block of SAR data can be assumed quasi-stationary in the azimuth direction.

Motion Parameter Estimation in the SAR System With Low PRF Sampling

A novel approach to motion parameter estimation with low pulse repetition frequency (PRF) sampling based on compressed sensing (CS) theory is introduced. As is known to us, when PRF is less than the Doppler spectrum bandwidth, moving targets suffer both Doppler centroid frequency ambiguity and Doppler spectrum ambiguity. Under this condition, the traditional parameter estimation method in the Doppler domain is out of action. The key of this letter converts motion parameter estimation in the synthetic aperture radar system with low PRF sampling into solving an optimization equation based on CS theory. Because moving targets in the scene can be regarded as sparse signals after clutter cancellation, an optimization algorithm based on CS theory is proposed to reconstruct sparse signals and meanwhile estimate the along-track velocities and azimuth positions of moving targets. Considering the fact that range cell migration of moving targets is not subject to PRF limitations, Radon transform is adopted to obtain unambiguous across-track velocities and range positions. Results on simulation and real data are provided to show the effectiveness of this method.

An Improvement in Multichannel SAR-GMTI Detection in Heterogeneous Environments

This paper deals with target-detection issues in extremely heterogeneous environments, with a multichannel synthetic-aperture-radar-based ground moving-target indication (SAR-GMTI) system, and proposes a new detector with the aim of addressing such extremely heterogeneous environments. The proposed detector is a multistage one: The first detection stage implements the conventional Displaced Phase Center Array test, but the second stage implements a new test, which is called the Degree of Radial-Velocity Consistency (DRVC) test. We will show that the newly developed DRVC test possesses two pronounced characteristics. The first characteristic is that the DRVC test incorporates such a priori knowledge that the radial velocities corresponding to the individual components of a moving target are all equal, while the second characteristic of the DRVC test is its clutter-heterogeneity-independent property. The two characteristics make the proposed detector a good candidate for addressing extremely heterogeneous environments. Simulation results demonstrate that the proposed detector outperforms several existing detectors, particularly in the capacity to handle extremely heterogeneous environments. Moreover, the application of the proposed detector to a set of real-measured three-channel airborne SAR-GMTI data further demonstrates the efficacy of the proposed detector.

Doppler Ambiguity Resolving in Compressed Azimuth Time and Range Frequency Domain

For high-quality synthetic aperture radar (SAR) processing, Doppler centroid ambiguity resolving is an essential procedure. A novel method for the resolution of Doppler ambiguity is presented which exploits the fact that, in the compressed azimuth time and range frequency domain, all targets span the same range frequency bandwidth and exhibit the same slope which is just proportional to the Doppler ambiguity number. The slope is removed by interpolation so that a simplified Radon transform can be applied. The use of entropy to find the maximum concentration of the Radon-transformed image can improve the robustness of the method. The proposed method directly gives a reliable estimate of the Doppler ambiguity number and is not affected by the azimuth partially covered targets. Experimental results show that the proposed method works well in medium- to high-contrast scenes.

Effects of Doppler Aliasing on Baseline Estimation in Multichannel SAR-GMTI and Solutions to Address These Effects

For multichannel synthetic aperture radar based ground moving-target indication (SAR-GMTI), the effective baseline usually needs to be estimated in order to obtain an accurate estimate of radial velocity for each moving target. This paper deals with the effects of Doppler aliasing on baseline estimation. We show that Doppler aliasing can introduce an interferometric phase uncertainty as well as an interferometric phase bias. The phase uncertainty will increase the variance of the baseline estimate, whereas the phase bias will bias the baseline estimate. To address the aforementioned effects caused by Doppler aliasing, a new method for estimating the effective baseline is proposed. One of the key steps of this method is to perform an operation called sample censoring aimed at mitigating the problem of estimation bias. The censoring threshold can be approximately determined by introducing a concept referred to as equivalent variance for the interferometric phases of the entire Doppler bins. Moreover, in order to account for the variation of interferometric phase variance over different Doppler bins, a strategy of weighting is adopted. Experimental results from SAR-GMTI data validate the effectiveness of the newly proposed baseline estimation method.

Adaptive MIMO radar target parameter estimation with Kronecker-product structured interference covariance matrix

Multiple-Input Multiple-Output (MIMO) radar with colocated antennas has an increased target parameter estimation performance, but at the cost of increased computational complexity. This paper first presents the conditions required for the interference covariance matrix (ICM) of colocated MIMO radar to take a special structure, namely a Kronecker product of some sub-ICMs, and then proves that based on this ICM structure, the conventional Minimum Variance Distortionless Response (MVDR) algorithm can be reformulated into a combination of three estimation algorithms all of much smaller scales, such that the computational complexity is decreased significantly. However, this ICM structure can be destroyed by inactive scattering sources, whose influence is studied via numerical experiments. It is found that inactive point scatterers can still be suppressed by adaptive algorithms relying on the ICM structure, on condition that the number is fewer than that of receiving antennas.

Improved DBF Algorithm for Multichannel High-Resolution Wide-Swath SAR

This paper deals with signal reconstruction for multichannel high-resolution wide-swath synthetic aperture radar (HRWS-SAR) systems. One of the commonly used algorithms for processing HRWS-SAR data is Kriegers digital beamforming (DBF) algorithm. This algorithm works quite well for cases with uniform space-time sampling as well as moderately nonuniform sampling. However, for cases with highly nonuniform sampling, Kriegers DBF algorithm in its original form suffers from a severe degradation in the signal-to-noise ratio, and for cases with coinciding sampling, this algorithm even fails to function. In this paper, we will solve these problems such that an improved DBF (IDBF) algorithm is developed. The key of the IDBF algorithm consists of two procedures: The first one implements an operation called ambiguity-index screening, which is based on two novel quantities, termed the equivalent sampling spacing and the effective reconstructed Doppler bandwidth; and the other key procedure implements a Doppler-spectrum weighting based on a newly defined parameter that is termed the maximum-to-minimum ratio of the noise spectrum. Simulation results show that the newly proposed IDBF algorithm shares a pronounced improvement in the imaging performance over Kriegers DBF algorithm. Moreover, simulation results also demonstrate that the IDBF algorithm exhibits a more robust and consistent overall performance than several other existing reconstruction algorithms.

High-Resolution SAR Imaging of Ground Moving Targets Based on the Equivalent Range Equation

In this letter, a novel ground moving target imaging algorithm suitable for high-resolution synthetic aperture radar (SAR) is proposed. The key step of the proposed algorithm is to make a moving target equivalent to a static one based on the derived equivalent range equation. Due to such equivalence, the commonly used standard algorithms for stationary scene imaging (e.g., the range Doppler algorithm) can be easily adapted to focus moving targets by adding only a search operation. The proposed algorithm does not make any approximation to the range equation and is thus rather suitable for high-resolution imaging of moving targets. In addition, due to the used equivalence, to focus a slow-moving target with four unknown parameters (two motion parameters plus two position parameters), the dimensionality of the parameter search space is reduced to one. Experimental results of the simulated data validate the proposed algorithm.

Parameter estimation of moving targets in the SAR system with a low PRF sampling rate

In the synthetic aperture radar (SAR) system with low pulse repetition frequency (PRF) sampling, it is difficult for the motion parameters estimation of the moving targets, because of the Doppler spectrum ambiguity and Doppler centroid frequency ambiguity of the echo signals. Considering that moving targets are sparsely distributed in the observed scene, their positions and velocities can be reconstructed by using the compressed sensing (CS) technique. In this paper, the range-walk correction are implemented by the Keystone transform and the sparse range-walk correction (SRWC), then the CS technique is proposed to reconstruct motion parameters by processing the azimuth signals of the moving targets. Experiments using the simulated and real data are performed, and the results confirm the validity of the proposed method.

A Knowledge-Based Target Relocation Method for Wide-Area GMTI Mode

This letter deals with the issue of moving-target relocation in wide-area ground moving-target indication for dual-channel radar systems. Due to channel mismatch, along-track baseline error, the existence of across-track baseline, etc., it is difficult to accurately relocate the detected targets. In this letter, we propose a new knowledge-based (KB) method for target relocation. The key idea of the proposed method is to use such knowledge that a moving target and its neighboring clutter, which is situated at the same azimuth angular position and the same range cell as this target in the observed scene, have the same interferometric phase. This new KB method, as an indirect one, does not employ the conventional relocation formula and therefore is not influenced by most of (if not all) interferometric phase errors. Experimental results from real radar data demonstrate a fairly high degree of target relocation accuracy.