Ruiqi Tian

A hybrid integration method of frequency agile radar for uniform moving target

Frequency agility (FA) is one of the important techniques in radar systems for the superiority in radar range, glint reduction, electronic counter-countermeasures and so on. However, frequency agility makes the signal processing complex and degrades the detection performance. For uniform moving targets, a hybrid integration method is proposed in group-group frequency agile radar (FAR). The Keystone transform is applied in each group for coherent integration. Due to the FA, a scale transformation based on linear interpolation is proposed, and then the trajectory feature of target is used to achieve the hybrid integration based on Hough transform. The experimental results validate the effectiveness and advantages of the proposed method.

A detection algorithm for radar weak targets under the interference of strong targets

In radar multi-target detection, the weak target might be interfered by the near strong target, which badly influences the detection of weak target. A novel detection algorithm for weak targets is proposed to cope with the situation above. Combining the Keystone transform and the Least Square (LS) filter, the return of strong target is reconstructed and then removed from the original. Finally, the weak target is detected by integration for the residual. The effectiveness of the proposed algorithm is illustrated and analyzed by simulations.

Real-time parameter extraction of the frequency agile PAR based on FPGA

According to the characteristic of a frequency agile radar, a fast method for parameter estimation of the direct-path signals is presented in this paper. In this method, the pulse width (PW) is roughly estimated based on the method in the frequency domain, and accurate PW parameter is estimated by matching the PW template. Second, accurate bandwidth (BW) is estimated and carrier frequency (CF) is roughly estimated based on de-chirp. Accurate CF is estimated by matching the CF template. Finally, parameter extraction algorithm of the paper is implemented on the FPGA hardware system. The test results of real data show that this method is highly accurate and computationally efficient. It has been successfully applied to an electronic reconnaissance system.

Moving target detection method for bistatic radar using random stepped-frequency chirp signal

Abstract. 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.

Velocity estimation of high-speed target for step frequency radar

Abstract. 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.

Target discrimination method for passive bistatic radar using narrowband and low-frequency illuminator

Abstract. 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.