Recently, Kikuchi et al. proposed a pair-matching method for two-dimensional (2-D) angle estimation using a cross-correlation matrix. Unlike some classical pair matching methods which require a complex process, Kikuchi's Method utilizes the corresponding combinations of the elevation and azimuth angles emerging in the cross-correlation matrix of two uniform linear arrays (ULAs) to achieve automatic pairing. However, Kikuchi's method has some drawbacks such as the pair matching and failure problems when the difference of the corresponding combinations of the 2-D angles cos cos =1 is small and the signal-to-noise ratio (SNR) is low. Furthermore, this method does not make good use of the cross correlation, where the effect of additive noise is eliminated, to improve the estimation performance. We propose a novel automatic pairing scheme for estimating 2-D angle by simultaneous singular value decomposition (SVD) of two cross-correlation matrices. Computer simulation results are presented to show that the proposed technique can overcome these problems and offer better estimation performance.

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In this paper, Delay and Doppler shift estimation of moving targets of OFDM based radar system by utilizing Maximum Likelihood Estimation(MLE) strategy has been produced. Taking benefits of OFDM waveform, the range Doppler coupling issues can be overcome for radar applications and complex balance filter is never again fundamentally used to adapt to frequency selective fading channel in view of multipath. Here Weighted Orthogonal Frequency Division Multiplexing (WOFDM) system is utilized, and the Delay and Doppler shift estimation of WOFDM is compared with Constant Envelope OFDM (CEOFDM). The comparing Cramer-Rao limits (CRB) for the parameters are derived. Weighted OFDM waveforms are planned with subject to limitations on peak to average power ratio (PAPR). For the delay estimation, The proposed WOFDM modulation have bring down CRB esteem compared with the great constant envelope OFDM regulation while meeting the prerequisite on the PAPR level.

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