Wenshuai Zhai

GROUND MOVING TRAIN IMAGING BY KU-BAND RADAR WITH TWO RECEIVING CHANNELS

Radar imaging experiment of ground moving target a light rail-way train by Ku-band radar with two receiving channels is introduced with imaging results presented. Both coherent and incoherent imaging as well as co-pol and cross-pol interferometric imaging were conducted with SAR amplitude images as well as interferometric-phase images obtained and compared. The along-track interferometric-phase images clearly show the speed variation of the train, i.e., the train traveled at an increasing speed in one direction and at a decreasing speed in the opposite direction. The incoherent imaging results indicate that for bistatic or multi-static radar imaging, the ultra-stable crystal oscillator (USCO) used by transmitter need not to be synchronized to the USCO used by receiver provided that the two basic crystal oscillators have small frequency difference and high stability. For better knowing the speed variation, Short Time Fourier Transform (STFT) is applied to the azimuthal signals to get the instant Doppler frequencies (IDFs), from which one can judge acceleration or deceleration status of the moving train. Electromagnetic scattering characteristics of the train are analyzed according to the SAR images. The estimated speed and length of the train are very well agreed with real situation.

Moving train imaging by ground-based Ka-band radar

Ground moving trains have been imaged by many airborne and spaccborne SAR systems, but seldom imaged by ground-based radar system. In this paper, we introduce our experiment on moving train imaging by a ground-based Ka-band radar system with 1GHz bandwidth. The 1GHz bandwidth is realized by synthesizing 10 subpulses in frequency-jumped burst (FJB). High-resolution SAR images for a moving train were obtained and the electromagnetic scattering characteristics were analyzed. Radar images show that at different aspect angle, the strong scattering centers are different and may changeable.

Moving target imaging by both Ka-band and Ku-band high-resolution radars

The experimental work on testing the wide-band transmitters and receivers developed for Ka-band and Ku-band radar systems, as well as the signal processing algorithms were introduced. A city light-railway train was selected as the imaged target. The wide-band transmitters and receivers were designed based on the stepped-frequency chirp signal (SFCS) with 2GHz bandwidth synthesized. The Super-SVA technique was used to deal with the case of transmitting SFCS with band gaps between subchirps for purpose of achieving the same bandwidth using as less as possible subpulses. Both Ka-band and Ku-band high-resolution radar images were obtained, which show that Ka-band images are much clear than that of Ku-band as we expect. There are two reasons to explaining this, one reason is due to the electromagnetic scattering of train itself are different for Ka-band and Ku-band frequencies, and the other reason is due to the interactions, i.e. multi-reflection or multi-scattering between the train and the side metal fences or the lamp post are different.

A prototype for stepped-frequency SAR dechirp imaging system and experimental verification

In SAR imaging, range resolution is inversely proportional to the transmitted signal bandwidth. Generally, for technological or cost reasons relative to radar hardware, the ability to produce or receive wide bandwidth signal is limited. However, if the frequency band of the transmitted signal is skipped within a train of sub-pulses and the received signals are properly combined, then the signal bandwidth could be effectively increased, as well as the range resolution could be improved. The proposed system indeed breaks through the limitation in range resolution which is set by the radar hardware units in traditional method. Synthesized processing of stepped-frequency chirp subpulses makes SAR range resolution much higher. The experiment has been conducted successfully and the improvement on range resolution is verified.

High-resolution compressive sensing imaging with stepped-frequency noise signal

High-resolution compressive sensing imaging with stepped-frequency noise signal (SFNS) is presented. The SFNS is similar to the stepped - frequency chirp signal (SFCS), which is also composed of a burst of subpulses with their carrier frequencies linearly increased or decreased, but each subpulse is a noise signal instead of a chirp signal. The noise signal of each subpulse is realized by Logistic mapping, i.e. it is a kind of chaotic signal or random like signal. Range compression for SFNS can be as same as that for SFCS when matched filtering (MF) is used. However when the compressive sensing (CS) approach is used, they are quite different. As for SFCS random sampling is performed to echoes of the subchirps while evenly sampling is performed for SFNS. Real data from a moving train is processed to demonstrate the effectiveness of both the signal model and the CS imaging algorithm.

A Ka-band high-resolution radar system and ground moving target imaging experiment

This paper introduces our recently upgraded Ka-band two-receiving-channel radar system, which adopts stepped-frequency chirp signal (SFCS) and the signal spans 2GHz bandwidth. The upgrading include the two-channel dechirping-on-receiving receiver and the data sampling and recording subsystem where high-speed optical transmission technique is used. We use two arbitrary waveform generators in the system, one for transmitting and another one for receiving, which provides us a great convenience for transmitting / receiving design. We briefly introduce the system design as well as discuss about the pulse compressing algorithm. In the outdoor experiment, buses, trucks and trains were taken as the ground moving targets to image and high-resolution images were obtained. The micro-Doppler phenomenon resulted from the rolling wheels is investigated.

Across-track interferometric SAR imaging experiment with multi-carrier frequencies

In this paper, we introduce the recently carried out airborne experiment with a Ku band multi-carrier-frequency interferometric SAR system. This system can work at three carrier frequencies, i.e. f1, f2 and f3 are 13.7GHz, 13.9GHz and 14.1GHz, respectively, each frequency channel has the same bandwidth of 220MHz. In the across-track experiment, very good interferometric phase images and mountainous topographies were obtained for three carrier frequencies. The recovered DEMs from three frequencies agreed with other very well. The obtained topographies of each carrier frequency agree with each other very well. Different filtering windows of 3, 5, 7 and 9 for denoising are applied to the interferometric phases and the corresponding DEMs are compared. It is shown that by combining the measurements of three frequencies, we can improve the accuracy of DEM without losing the spatial resolution.

Apply super-SVA to Stepped-frequency chirp signal processing based on dechirp method

Stepped-frequency chirp signal (SFCS) is an important signal form used for high-resolution radar. It contains several sub-chirp signals with stepped carrier frequency and can be synthesized to a wide-band chirp signal. Dechip method is a quick, effective method to process SFCS, it synthesizes the sub-pulses of SFCS in time-domain. The usual design rule of SFCS is the frequency step (Δf) must be less than the bandwidth of sub-chirp (Bm). If Δf > Bm, the synthesized signal will have gaps, which leading to grating lobes in radar image. Here we proposed an algorithm by using Super-SVA to extrapolate each sub-pulse so as to fill the gaps and depress grating lobes. Without the restriction of Δf < Bm, it will be very helpful for using less sub-chirps to obtain higher resolution and reducing the influence of target motion on the quality of synthesized signal. We presented simulations to verify the proposed algorithm. Furthermore the results imply that super-SVA can not only be used for frequency-domain extrapolation, but also time-domain extrapolation of chirp signal.

A sparse optimization method for masking effect removal in noise synthetic aperture radar

In this paper, we propose a sparse optimization method to suppress the masking effect of noise synthetic aperture radar (SAR) imaging. The transmitted noise waveforms have large fluctuations in the spectrum, which results in high-level sidelobes in the range direction. Weak targets can be masked by the sidelobes of strong targets when traditional matched filtering (MF) is applied. Inspired by the idea of compressed sensing (CS), we formulate the noise SAR imaging process as solving an inverse problem from incomplete random frequency measurements, and then reconstruct the noise SAR image using sparse optimization method. Experimental results on real airborne noise SAR data are presented to show the effectiveness of the proposed method.

ISAR imaging of multiple targets based on sparse representations

This paper proposes a new method for inverse synthetic aperture radar (ISAR) imaging of multiple targets based on sparse representations. The proposed method includes three steps: (1) coarse estimation of the radial velocities of the targets using Radon transform; (2) signal separation of different targets using sparse representation (SR) method; (3) refocusing of each targets using traditional range-Doppler algorithm. The effectiveness of the proposed method is verified using real ISAR data.