Medium-earth-orbit (MEO) synthetic aperture radar (SAR) has the advantages of short revisit time and wide coverage. Moreover, it has a high orbit altitude, and thus can be used to perform air moving target indication (AMTI) missions. Nevertheless, the velocities of air moving targets are usually high, which will make them suffer severe defocusing in the SAR image focused according to the stationary scene parameters, and thus brings many difficulties to the design of AMTI methods. This paper studies air moving target signal modeling in image domain for MEO SAR. Air moving targets are divided into three types according to the residual range migration and Doppler ambiguity, and their analytical expression in the image domain are derived respectively. Numerical results verify the correctness of the derived signal models.

This paper proposes a new method for parameter estimation in the azimuth frequency domain, which can accommodate lower signal-to-noise ratios (SNR). By compensating for azimuth compression, range walk, and range curvature simultaneously, the SNR of signal is improved, so as to complete the range cell migration correction. Previously, we first compensated for the ambiguity velocity in the azimuth time domain to avoid aliasing and ambiguity in the frequency domain. Finally, we use cubic phase function and Radon transform to estimate the polynomial phase signal. Numerical results validate the proposed method.

This letter studies the issue of ground accelerating target imaging with airborne circular stripmap synthetic aperture radar (CSSAR). Most of the existing ground moving target imaging algorithms are based on the Taylor approximated range model. However, for CSSAR and accelerating targets, the high-order terms of the Taylor series should be kept to meet the requirement of high-quality imaging, which would complicate the imaging process. In this letter, a more accurate approximation, i.e., the Chebyshev polynomial approximation, is made to the target’s range equation, which reduces the number of parameters to be searched or estimated during imaging. Moreover, to deal with the Doppler ambiguity and range migration caused by the target’s unknown motion, an azimuth-time and range-frequency domain-matched filtering-based imaging method is proposed. Furthermore, the differential evolution (DE) algorithm is adopted to achieve an efficient search of the parameters of the Chebyshev polynomial approximated range model. Finally, numerical experiments are conducted to validate the proposed method.

The omega-K algorithm ($\omega $KA) is an accurate imaging method for squinted synthetic aperture radar (SAR) with linear trajectory. However, for SARs with curved trajectory, since it does not allow the radar velocity to vary with range, the imaging quality would degrade severely. To address this issue, an improved$\omega $KA is proposed in this letter. We design a special Stolt mapping to avoid the complex additional range cell migration (RCM) and the skew of the data support region. Then, the RCM correction (RCMC) and azimuth compression are operated in the range Doppler domain. With these improvements, the radar velocity is allowed to vary with range, which greatly reduces the phase error in the case of large range swaths. Numerical results validate the proposed algorithm.

Air moving target indication (AMTI) is an important task of spaceborne radar. Medium-Earth-orbit (MEO) synthetic aperture radar (SAR) has the characteristics of large coverage, short revisit time, and high orbital altitude, and thus is an attractive tool for AMTI missions. However, due to air moving target’s high-speed maneuvering and MEO SAR’s long synthetic aperture time and significant curvature of trajectory, the signal of air moving target after imaging processing is very complex, which makes the design of AMTI method be challenging. In this article, a study on image-domain signal modeling and refocusing of air moving target for MEO multichannel SAR is presented. The range equation of an air moving target with 3-D velocities and accelerations is established. In addition, the target’s signal models after range migration correction and azimuth compression with the stationary scene parameters are derived. Then, via dividing targets into three types based on their residual range migration and Doppler ambiguity, the image-domain signal models of air moving targets are developed. Furthermore, a refocusing method that can cope with large range migration and Doppler ambiguity is proposed. Finally, numerical experiments are conducted to validate the developed signal models and proposed refocusing method.

The clutter suppression methods based on post-Doppler space time adaptive processing technology is a hot search topic in recent years. However, to coherently integrate a target’s energy of each channel, these methods require searching target’s velocities, which may introduce a large computation load. This paper proposes a method for calculating the optimal velocity search step of adaptive clutter suppression for the commonly used three-channel synthetic aperture radar (SAR) ground moving target indication (GMTI) systems. First, the signal models in the range Doppler domain are developed. Then, based on the fact that the signal-to-clutter-noise ratio loss of clutter suppression and the coherent integration gain loss are all introduced by the mismatch of the steer vector, the way to obtain the analytical expression for calculating the optimal velocity search step is developed. Experimental results validate the propose method.

This paper studies the range equation modeling of a ground moving target for distributed multichannel medium Earth orbit synthetic aperture radar (SAR) ground moving target indication (GMTI). A third-order approximated range equation for each channel is established. Then, the range equation is simplified, and a more concise range equation model is derived, which will benefit the design of SAR-GMTI methods. Finally, through numerical simulation, the derived range model’s accuracy and scope of application in different baseline lengths and wavelength bands are studied.

This paper proposed an efficient imaging method for medium-Earth-orbit (MEO) synthetic aperture radar (SAR) ground moving target indication (GMTI) systems. MEO SAR is an attractive tool for GMTI applications, because of its advantages of large coverage, short revisit time and strong damage resistance. In this paper, first, the third-order Taylor-approximated range model of a moving target for MEO SAR is developed. Then, based on the proposed range model, the target's 2-D spectrum is derived and a novel imaging method is proposed. The proposed imaging method implements focusing without a priori knowledge of targets' motion parameters and position parameters. Finally, numerical results validate the proposed method.

This paper presents a study on signal modeling for airborne multichannel circular stripmap synthetic aperture radar (CSSAR)-ground moving target indication (GMTI) systems with relatively high resolution. High resolution is an important trend of synthetic aperture radar (SAR), which means higher accuracy requirement of range history and longer synthetic aperture time. It's known that targets are probably experience accelerations as the synthetic aperture time increases. Therefore, compared with the systems of lower resolution, the target signal modeling of high-resolution systems becomes more challenging. Besides, the coupling relationship among a target's motion and position parameters becomes more complicated due to the existence of accelerations. In this paper, a fourth-order range history model of a moving target is developed. Moreover, the target signal model is established, and the along-track interferometric (ATI) phase history is derived to reveal the coupling relationship among a target's motion and position parameters.

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.

This paper proposes a new scheme of motion parameter estimation and relocation for airborne three-channel circular stripmap synthetic aperture radar (CSSAR)-ground moving target indication (GMTI) systems. Compared with the conventional straight-path SAR, the parameter estimation of a target is more challenging because the target's range history and signal model are more complicated due to the complexity of the relative motion between CSSAR and ground moving target. In this paper, the signal model of a ground moving target and the expression for its along-track interferometric (ATI) phase from the environment of airborne three-channel CSSAR are derived. The coupling effect among the target's motion and position parameters is also figured out. Then, a scheme of motion parameter estimation and relocation is proposed. The proposed scheme utilizes the ATI phase and the quadratic-term coefficient in the range equation to estimate the target's motion and position parameters and utilizes an iterative strategy to address the coupling effect among these parameters. Numerical simulations are conducted to validate the satisfactory performance achieved by the proposed algorithm.

We present a new algorithm for suppressing azimuth ambiguities when measuring surface currents with an along-track interferometric (ATI) synthetic aperture radar in heterogeneous scenes, such as coastal waters or rivers. The key of the proposed algorithm involves a careful analysis of a parameter called the eigenvalue spectrum entropy (EVSE), which is defined as the entropy of the eigenvalue spectrum of the ATI covariance matrix computed in the Doppler domain. The physical meaning of EVSE is that it serves as a descriptor for the degree to which an unambiguous signal component and an ambiguous one are mixed. With the help of EVSE, azimuth ambiguities can be suppressed. Simulation results demonstrate that as compared with the conventional ATI method without azimuth ambiguity suppression, the proposed algorithm allows for a pronounced improvement in the current measuring accuracy. Other advantages of the proposed algorithm lie in the fact that it is not only adaptive, due to its ability to automatically capture the useful Doppler band whose width and position may both vary for different radar and scene parameters, but it also needs a minimal number of user inputs, making it a quite attractive algorithm for routine implementation.

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.

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.

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.

For interferometric synthetic aperture radar (InSAR), the second moment of interferometric phase, i.e., its variance, is a useful metric for InSAR applications (e.g., configuration design). Due to the high degree of nonlinearity in the probability density function of the multilook interferometric phase, it is extremely difficult to derive the analytical expression of the interferometric-phase variance as a function of the number of looks. However, in this letter, we will show that, if we follow an indirect route, then an analytical formula for approximating the interferometric-phase variance for any number of looks can be obtained. The key step of deriving this analytical formula is to transform the interferometric phase into the Euler domain. Simulation results show an excellent agreement between the measured variance curve and the curve obtained by the newly proposed formula except for some small coherence values.

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.