Wideband Digital Array Radar Channel Equalization Algorithm

Wideband Digital Array Radar (WDAR) is a fully digitized array antenna radar in which wideband signal waveform is transmitted and digital beamforming (DBF) technology is used in receiving and transmitting. digital phased array technology, wherein transmit and receive signals are digitized near the antenna element, can offer significant advantages. such as achieving high dynamic range (DR), achieving high resolution, multifunction, rapid multi-beams steering, low sidelobes, multi-targets, anti-jamming, Adaptive Processing, target identification and discrimination.Most of functions are done in signal processors. Therefore, it is assured that amplitude and phase of the digital baseband signals of the elements are the same with received signal in the antennas. This requires that array channels are distortionless across the entire signal bandwidth and frequency responses are identical for all channels. But the change in the characteristic of analog devices and circuits in the element channels will cause the frequency-dependent amplitude and phase difference of receiver channels and transmitter channels in WDAR. The difference among the frequency responses of the channels are called channel mismatch. Channel mismatch will affect seriously superior performance of the WDARIn this dissertation, channel mismatch is investigated in detail. Impact of the mismatch on WDAR's performance is analyzed. Adaptive channel equalization in order to compensate for channel mismatch are investigatedFirst of all, four channel mismatch models are described. Mathematic expressions of channel frequency response are presented. Compares are drawn among the models, Method for using the models in simulation is presented.Then, impact of the amplitude and phase error in the channel on radar echo signal is analyzed by using sine ripple model. Impacts of different channel error on digital beamforming and pulse compress are analyzed by the control of sine ripple model parameters. Showing that impact of mismatch on low-sidelobe beams is serious. This requires precise control of the radar receiver's frequency response across the entire signal waveform bandwidth in order to achieve low beam sidelobes and low time (ie. range) sidelobes.Two channel equalization algorithms, named frequency-domain based and time-domain-based algorithm, are investigated for compensating for channel mismatch. channel equalization time-domain-based algorithm are based on Weiner filter theory and Least Squares theory. Basic algorithm of the time domain equalization is presented. Impact of parameters on equalization performance is discussed in detail. Results of simulation are shown that the sampling rate, number of taps, SNR will affect seriously equalization performance. The results are presented in detail. Since the frequency response is time-varying, LMS and RLS adaptive algorithm are described for the sake of equalization adaptively. Algorithm flows are presented.Finally, frequency-domain based channel equalization algorithm is investigated. Basic algorithm is presented based on least squares fitting method. It is show that frequency response mismatch is more serious in the skirts than band center, especially in the environment of low SNR. Two modified methods are presented. One is weight least squares fitting method, and diagonal elements are the reference channel magnitude response. Another is selecting equalization bandwidth. Good equalization performances are achieved by using two methods. Impacts of many factors on equalization performance are analyzed. such as the abnormal extent of frequency response of the receiver channel, Bandwidth-Time delay product, FFT-points. Moreover, Two implementation methods of equalizer are presented. The relation between frequency-domain based and time-domain-based algorithm are derived, some compares are drawn between two algorithms.