KEYWORDS: Target detection, Radar, Signal detection, Doppler effect, Synthetic aperture radar, Signal to noise ratio, Fourier transforms, Numerical simulations, Monte Carlo methods, Baryon acoustic oscillations
As random stepped-frequency chirp (RSFC) signal is used in wide-band radar applications such as synthetic aperture radar (SAR) and inverse SAR. RSFC has advantages over the linear stepped-frequency chirp, including suppressing the range ambiguity, decoupling the range-Doppler coupling, and reducing the signal interference. RSFC is usually descrambled and then fed to the inverse fast Fourier transform (IFFT) to achieve a coherent integration as well as a high-resolution range. However, this method needs frequency descrambling and accurate velocity pre-estimation for moving target detection. We propose a coherent integration method based on time-dechirping for bistatic radar. This method can detect moving targets without frequency descrambling or accurate velocity pre-estimation. This paper first models the target echo mathematically and outlines the difficulties associated with the processing of IFFT for RSFC. Then the detailed principles of the proposed method are introduced and the flowchart is given. Finally, numerical simulations are conducted to verify the effectiveness of the proposed method and show its detecting ability in the presence of noise.
Aiming to precisely estimate the velocity of high-speed targets for step frequency (SF) radar, a positive–positive–negative SF waveform consisting of two continuous positive SF pulse trains and a negative one is designed, and a velocity estimation method is proposed based on two-dimensional time-domain cross correlation (2-D TDCC). Making full use of the characteristics of the designed waveform, the coarse velocity estimation is achieved by 2-D TDCC of positive–positive SF pulse trains and then the Radon transform is applied to solve velocity ambiguity for high-speed targets. After velocity compensation for positive–negative SF pulse trains, the velocity residual is estimated precisely by 2-D TDCC. Simulation results show that the proposed method exhibits good performance for estimation accuracy, stability performance, computational complexity, and data rate by comparisons.
As most illuminators of opportunity are relatively narrowband and of low-frequency, passive bistatic radar (PBR) is so weak in target discrimination that it can hardly distinguish adjacent aircraft or ships. To solve this problem, we propose a matched filter-based method. This method uses the bistatic range of the target to construct the corresponding filter groups and then produces a two-dimensional image by correlating the echo signals. We finally convert the target discrimination problem to distinguish the peaks in the image. The proposed method overcomes the target discrimination problem for PBR using the narrowband and low-frequency illuminator. Simulation results indicate the effectiveness and validity of the proposed method in distinguishing adjacent targets.
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