Hong Gu

Application of the fractional Fourier transform to moving target detection in airborne SAR

As a useful signal processing technique, the fractional Fourier transform (FrFT) is largely unknown to the radar signal processing community. In this correspondence, the FrFT is applied to airborne synthetic aperture radar (SAR) slow-moving target detection. For airborne SAR, the echo from a ground moving target can be regarded approximately as a chirp signal, and the FrFT is a way to concentrate the energy of a chirp signal. Therefore, the FrFT presents a potentially effective technique for ground moving target detection in airborne SAR. Compared with the common Wigner-Ville distribution (WVD) algorithm, the FrFT is a linear operator, and will not be influenced by cross-terms even if multiple moving targets exist. Moreover, to solve the problem whereby weak targets are shadowed by the sidelobes of strong ones, a new implementation of the CLEAN technique is proposed based on filtering in the fractional Fourier domain. In this way strong moving targets and weak ones can be detected iteratively. This combined method is demonstrated by using raw clutter data combined with simulated moving targets.

Random signal radar - a winner in both the military and civilian operating environments

Besides some general requirements, modern military radars should possess excellent LPI (low probability of intercept) properties. And civilian radars should satisfy the rigorous requirement of EMC (electro-magnetic compatibility) performance. The special features of random signal radar are analyzed here based on the different requirements for military and civilian use. Results show that random signal radar has excellent LPI property and EMC performance simultaneously, which can satisfy both military and civilian requirements.

Multi-SVD based subspace estimation to improve angle estimation accuracy in bistatic MIMO radar

A new multi-SVD based subspace estimation algorithm is proposed to improve the direction of departure (DOD) and direction of arrival (DOA) estimation accuracy for bistatic multiple-input multiple-output (MIMO) radar. First, the matched filter output is transformed to a 3-order tensor. Then the signal subspace is estimated by multi-SVD of the matrix unfoldings of this tensor or its covariance tensor. Since the multidimensional structure is utilized, the estimated signal subspace of our method has better accuracy than that of the traditional SVD/EVD method. Combined with the classical subspace based methods, such as MUSIC and ESPRIT, the proposed approach improves the angle estimation performance compared with the existing ones. Simulation results confirm the effectiveness of our method.

The analysis and design of modern Low Probability of Intercept radar

In the modern battlefield, radar faces more and more serious threats from ECM and ARM, etc. Only the Low Probability of Intercept (LPI) radar can survive. In this paper, the principle of LPI radar is introduced first. Then the effects of radar parameters on LPI performance are discussed in detail. Finally, some advice is proposed for the design of the ideal LPI radar system.

Joint 4-D Angle and Doppler Shift Estimation via Tensor Decomposition for MIMO Array

A joint 4-dimensional (4-D) angle and Doppler shift estimation method is proposed for bistatic multiple-input multiple-output (MIMO) uniform rectangular array (URA). The key idea behind the proposed approach is to use tensor decomposition to estimate the target parameter matrices, and use Vandermonde structure enforcing strategy to regress the parameters. This algorithm can effectively estimate all the parameters simultaneously, and requires neither parameter pairing nor multi-dimensional nonlinear peak searching.

Ground maneuvering target detection based on discrete polynomial-phase transform and Lv's distribution

Abstract In a synthetic aperture radar (SAR) system, prolonging the integration time can improve the detection performance of the ground moving target. However, the complex motions of the target will induce severe range migration and Doppler frequency migration (DFM), which cause target energy defocused and deteriorate the imaging quality. In order to deal with the problem, a novel ground moving target focusing method is proposed. In this paper, the discrete polynomial-phase transform (DPT) is performed to reduce the phase order of the range compressed signal. Then, the residual range walk is removed by the constructed compensation function. Lastly, Lvs distribution (LVD) is used to motion parameter estimation and DFM correction. The proposed method is capable of focusing the targets both near and apart from the scene center and is computationally efficient. Several simulation results validate the effectiveness of the proposed method.

Sensor Gain-Phase Errors Estimation Using Disjoint Sources in Unknown Directions

Sensor gain-phase error estimation is necessary for equipment using sensor array, such as radar, sonar, and mobile communication before they come into service. Due to this requirement, we propose an offline calibration algorithm for sensor gain-phase errors using two auxiliary sources, which appear independently of both space and time, named disjoint sources. The significant superiority of this algorithm lies in the use of calibration sources in unknown directions. First, based on the data covariance matrix, the sensor phase errors are obtained, and the relation between phase error matrix and array manifold is established. Second, the directions of two disjoint sources are obtained by the way of 2D search based on eigen-structure subspace method. Third, we provide two methods to realize the algorithm. The proposed algorithm performs independently of phase errors. Moreover, the accurate direction measurement of calibration sources is not necessary. Computer simulations are shown to verify the efficacy of the proposed algorithm.

Fast method for radar maneuvering target detection and motion parameter estimation

The detection of maneuvering targets is a challenging task for radar. There are the first-order range migration (FRM), second-order range migration (SRM) and third-order range migration (TRM) which respectively caused by the velocity, acceleration and jerk of the target, and they will affect the performance of energy accumulation. In order to resolve the problem, the third-order keystone transform (TOKT) is employed to correct TRM in this paper, then FRM and SRM are removed simultaneously through frequency shift and cross correlation. After RM correction, the velocity and acceleration are estimated via Lv’s distribution (LVD). Finally, the jerk is estimated through a searching procedure. Compared with some existing methods, the proposed method has a better integration performance and a lower computational cost, and can be applied to estimate the motion parameters of multi-targets. Several simulation results are provided to validate the effectiveness of the proposed method.

The study on Doppler centroid estimation in DBS imaging

Doppler centroid estimation is one of the most important steps in Doppler beam sharpen (DBS) imaging of airborne pulse Doppler radar. Two improved Doppler centroid estimation techniques are proposed. They are called the weighted pattern match technique (WPMT) and curve fitting iterative technique (CFIT) respectively. These new algorithms avoid the effects of non-homogeneous scene and random fluctuation of echoes. The precision of the estimation is improved significantly. The processing results of raw radar data prove their effectivity.

A performance analysis of the MUSIC algorithm in the presence of amplitude and phase errors

This paper presents an analysis of the effects of amplitude and phase perturbation on the spectrum of the MUSIC algorithm. Theoretical expressions of the mean and variance of the spatial spectrum are derived, that is, we quantify the sensitivity of the MUSIC algorithm by first- and second-order statistical analysis. The expression reveals the relationship between the error of spectrum and the variance of the perturbation. The performance prediction is validated by computer simulation. The amplitude and phase perturbation decrease the peak values of the spectrum obviously and lower the resolving power, and the amplitude perturbation can result in spectrum error greater than that of phase perturbation for the case of the same variance of modeling errors.