Bao Zheng

Micro-Doppler analysis and imaging of air-planes with rotating parts

In ISAR imaging of air-planes with rotating parts, the micro-Doppler phenomenon induced by the rotors will generate side-bands about the rigid body image. This paper derives the imaging model and analyzes the micro-Doppler of rotors. Then, a method for micro-Doppler separation based on low chirp rate matching is proposed. Meanwhile, an algorithm for scaling the 2D imaging of rigid body is presented, based on the complex-valued back-projection algorithm. Similarly, ISAR imaging of the rotating rotors can be obtained through the same algorithm. Finally, images from the rigid body and the rotating rotors are merged together to obtain a full image of the air-plane. The validity of the proposed algorithms has been proved by simulations.

Imaging study of high squint SAR based on FMCW

This paper establishes the model of high squint FMCW SAR received signal, analyzes its characteristics, and posts the Doppler frequency shift effect induced by the continuous motion in range direction while radar transmitting and receiving signal. Meanwhile, this paper proposes a modified RD algorithm (RDA) aimed at high squint FMCW SAR dechirp-on-receive data, which compensates for range walk in the time domain, Doppler frequency shift and range curve in the frequency domain. Point target simulation verifies the analysis and validity of the proposed algorithm. In addition, for the Doppler frequency shift induced by the continuous motion while radar transmitting and receiving signal, this paper also analyses its effect on image.

Radar target recognition by a logarithm bispectrum-based method

The paper starts with the definition of logarithm bispectrum and the presentation of its properties relative to target recognition. A relationship is established between the logarithm bispectrum feature of a target and that of the higher resolution range profile. As a result, the criterion for target recognition, based upon the relationship, is induced and its implementation is given. Simulation with some out-field acquired data is given to show that the approach is effective and advantageous over an existing one for rapid recognition.

Coherent single range Doppler interferometry algorithm for high-speed spinning targets 2D imaging

This paper focuses on the narrow band radar imaging for high-speed spinning targets. Based on the time-frequency characteristic of the echoed signal, a novel coherent spectrogram redistribution method, coherent single range Doppler interferometry (CSRDI), is proposed, which is of high resolution and robust even in the case of the low signal-to-noise ratio. The spinning rate error is also taken into consideration and an estimating approach based on the focal entropy is proposed. The validity of the approaches is confirmed by Numerical simulations.

Adaptive S-method based ISAR imaging of maneuvering targets

The range-Doppler imaging algorithm is a basic method for ISAR imaging, which is based on the uniform rotation of a target in a fixed plane. For maneuvering target, however, its rotational velocity and the axle often vary with time, so the second-order phase terms are induced to target echoes. Aimed at this situation, an adaptive S-method based imaging algorithm is proposed in this paper. First, translational motion compensation is implemented to the raw data. Then, this algorithm is applied to the echo of each range cell, to eliminate second-order phase terms and obtain ISAR imaging in the range frequency-Doppler domain. Since it only requires complex multiplications and adding, this algorithm has low computational complexity in practical use. In addition, due to the adaptiveness, it can adjust itself according to the returned signals, and reduce the influence of cross-terms for each range cell at the same time. The measured data has proved the validity of this algorithm.

One dimensional cross-range imaging and methods to improve the resolution of low resolution radar targets

One dimensional (1D) images can be used to characterize the major features of the target and serve for the purpose of automatic target recognition (ATR). For conventional low resolution radar, 1D range profiles cannot be measured, but 1D cross-range images can be obtained by processing a sequence of radar echoes. There have been few papers in the literature discussing how to obtain 1D cross-range images, but the image resolutions obtained are low, and even some wrong images were obtained because of the following two reasons: one is that translational motion compensation (TMC) is not correct; the other is that 3D and nonuniform rotational motions are not considered. In this paper we propose new methods to tackle these two problems. First we use the minimum entropy method to compensate the translational motion. Second, based on the observation that the scatterer sub-echoes are not sinusoidal and should be approximated as linear frequency modulation (LFM) signals after TMC due to the 3D and nonuniform rotation of the target, we propose an extended RELAX high resolution method to estimate the multicomponent LFM signals, and obtain dynamic instantaneous 1D cross-range images. The methods are evaluated using both simulated data and real radar data.

Joint power and bandwidth allocation for centeralized target tracking in multiple radar system

A scheme of joint power and bandwidth allocation (JPBA) for centralized target tracking in multiple radar system is proposed in this paper. The Bayesian Cramér-Rao lower bound gives a measure of the best achievable performance for target tracking. Hence, it is derived and utilized as an optimization criterion for the JPBA strategy. Simulation results show that the proposed algorithm significantly outperforms equal power allocation, in terms of the tracking root mean square error.

Experimental reaserch of unsupervised Cameron/ML Classification method for fully polarimetric SAR Data

Fully PolSAR data provided by the NASA/JPL laboratory are widely used to classify PolSAR image. In this paper, an unsupervised Cameron/ML approach is proposed to classify airborne fully polarimetric data collected by a research institute in China. Camerons method is used to initially classify the PolSAR image firstly. Secondly the initial classification map defines training sets for the maximum likelihood (ML) classifier. The classified results are then used to define training sets for the next iteration. The advantages of this method are the automated classification, and the interpretation of each class based on scattering mechanism. Formula of Cameron classification for the very measured data is also obtained here. The experiment demonstrates the proposed approach dramatically improves the classification result compared with the Cameron method.