Zhaoda Zhu

ISAR motion compensation using modified Doppler centroid tracking method

With regard to the phase compensation in inverse synthetic aperture radar (ISAR), the modified Doppler centroid tracking (MDCT) method is developed which applies the phase gradient autofocus (PGA) algorithm developed by Wahl (1994) to improve the Doppler centroid tracking (DCT) method. When the phase compensation is performed, the proposed approach smartly eliminates the effect of the rotational phase component (RPC) on the estimation of the translational phase component (TPC) by circular shifting, windowing and iteration steps. After several iterations, the maximum likelihood estimation and compensation of the TPC of the target can be realized more effectively. The processing results of live data show that the proposed method can improve the imaging quality of ISAR significantly.

Cross-range scaling of inverse synthetic aperture radar

This paper investigates the problem of cross-range scaling of inverse synthetic aperture radar. It is very important to target classification and recognition via ISAR. The cross-range scale of ISAR depends on both radar wavelength and rotating angle of target relative to radar-line-of-sight (RLOS) during the total coherent processing time. The former is known while the latter is difficult to determine especially in the case of ISAR. In this paper, a new approach, which is based on the principle of tomographic imaging and the property of the coherent processing of echo data, is developed to estimate the rotating angle of target relative to RLOS during the total coherent processing time. As such,it is able to carry out the cross-range scaling of ISAR. The proposed approach is used to process the computer simulated data and the real data of model B-52 collected in a microwave anechoic chamber. The processing results show that the proposed approach is correct and effective.<<ETX>>

Multiple moving target resolution and imaging based on ISAR principle

The fine relative motion strongly affect the resolution capability of standard ISAR processing for multiple moving targets without gross relative motion. For multiple targets with gross relative motion, two methods, based on time-frequency analysis and maximum likelihood principle respectively, are proposed to resolve and image the targets. Simulation results to verify the methods are also given.

Radar imaging using linear prediction for data extrapolation

The authors describe an investigation wherein the resolution capability of range-Doppler imaging radars is extended well beyond the limitation imposed by the conventional FFT (fast Fourier transform) range-Doppler processing. The approach adopted uses linear prediction for data extrapolation before performing Fourier reconstruction. Preliminary results of rotating platform imaging based on experimental data acquired in a microwave anechoic chamber show that this technique shows promise for improving the resolution capability of range-Doppler imaging radars. With this approach, one can obtain either higher-resolution images for the same effective bandwidth of transmitted signals and total rotation angle in imaging, or equivalent-quality images from a smaller bandwidth and rotation angle.<<ETX>>

Analysis of extended target detectors

This paper views the problem of extended target detection as that of detection based on multi-observations, and points out that extended target detection for single pulse is similar to multi-pulses detection for low resolution radar. The only difference between them is that the latter is a process of accumulation along time (from pulse to pulse), while the former is the one along range (from cell to cell). By the virtue of the well developed theory of low resolution radar detection, the paper gives the conditions for which existing extended target detectors are suited. The performances of the detectors are compared. Thus, the domain of detection is extended from space (range) to frequency, and a HRR detector for multiple pulse is presented.

High resolution radar detection based on fractal dimension

It is difficult to design a detector for high resolution radar because of the time variability and non-linearity (or non-Gauss) of radar clutter and target. Recently someone proposed a method of signal detection based on fractal dimension. The basic idea is to decide whether there is a target or not by using the difference of fractal dimension between signal and interference (including clutter and noise). Firstly this paper studies the fractal dimension of range profiles of B52 plane model at different aspect obtained in microwave anechoic chamber. Then it models fractal dimension as a random variable, and designs a likelihood ratio detector based on fractal dimension. The performance of this detector is analyzed by statistic theory instead of Monte-Carlo simulation.

Two improved methods of motion compensation for 1D cross-range ISAR imaging

In this paper, the problem of motion compensation and imaging in one-dimensional (1D) cross-range domain is investigated. Two methods of motion compensation are developed. They are the maximal peak (MP) and the maximal burst integral (MBI). Their advantages over the existing approaches are simple in computational complexity. The imaging results of the electromagnetic simulated data and the live data of narrowband coherent radar are obtained by use of the proposed methods.

Comparison study on high resolution radar target recognition

This paper studies high resolution radar target by range profile. Three methods of recognition are tested using the data of an off-line ISAR experiment. They are two correlation filters (one in space domain (range) and another in frequency domain) and radial basis function (RBF) network in frequency domain. The ratios of recognition for three methods are given for different SNR.

Efficient computation of the 2-D discrete pseudo-Wigner distribution by the fast Hartley transform

Wigner distribution (WD) is useful in analyzing and processing nonstationary signals. In this paper the fast Hartley transform (FHT) approach for computing the one-dimensional discrete pseudo-Wigner distribution (1D DPWD) is extended to compute the two-dimensional (2-D) DPWD and a new fast algorithm is presented for computing the 2-D DPWD by the 2-D FHT entirely in the real domain. First, the original 2-D real signal is converted into its complex analytic version. A fast algorithm is proposed to compute the 2-D discrete Hilbert transform using the 2-D FHT instead of the 2-D complex FFT with a reduced number of real operations. Then, the algorithm formulae are derived for computing the 2-D DPWD of the analytic signal by the 2-D FHT. Compared with the conventional FFT approach, the proposed algorithm is performed entirely in the real domain, and the computational complexity is greatly reduced from 3 2-D complex FFTs to 3 2-D real FHTs.

An improved approach of cross-range scaling in ISAR

We have developed an approach of ISAR cross-range scaling. The fundamental principle is that we can estimate the rotating angle of target relative to radar-line-of-sight (RLOS) during the total coherent processing interval via the tomographic formation. However, the multi-dimensional search involved in the estimation of rotating angle will result in huge computational load. In this paper, an improved approach of cross-range scaling in ISAR is presented which takes the place of tomographic formation with the extended coherent processing and modifies the criterion to search the rotating angle. The processing results of computer simulated data and real data of model B-52 collected in a microwave anechoic chamber show that the improved approach is able to carry out the cross-range scaling of ISAR accurately. As compared with the previous method, its computational complexity is greatly reduced.