Abstract
We focus on the range migration (RM) and Doppler frequency migration (DFM) corrections in the long-time coherent integration, and a fast detection method based on two-dimensional trilinear autocorrelation function is proposed for the maneuvering target with jerk motion. This proposed method can integrate the echoes’ energy into peaks in a three-dimensional parameter space coherently and estimate the target’s radial range, acceleration, and jerk simultaneously by the peak detection technique. Then through the estimations of radial range, acceleration, and jerk, the radial velocity can be obtained through one-dimensional parameter searching. Finally, RM and DFM can be compensated simultaneously, and the target can be detected through the constant false alarm technique. This proposed method can strike a good balance between the computational complexity and detection performance. Experiments with the simulation and real measured radar data are conducted to verify the proposed method.
Highlights
Maneuvering target detection and motion parameters estimation are important applications of radar, the study on these aspects has received wide attention in the past decades.[1,2,3,4,5,6,7,8,9,10] With the development of science and technique, the target’s radar cross section becomes lower and lower, and the radar detection performance is affected
Based on the consideration of improving the balance between the computational complexity and detection performance for the methods constructing the autocorrelation functions (AFs) in the slow time domain, a coherent detection method based on two-dimensional (2D) trilinear autocorrelation function (TAF) is proposed in this paper
For the method in Ref. 20, the ACCF iteratively, ACCF-LVD, and the proposed method, some output signal-to-noise ratio (SNR) losses are caused by the nonlinear AFs, their detection performances are worse than the generalized RFT (GRFT)
Summary
Maneuvering target detection and motion parameters estimation are important applications of radar, the study on these aspects has received wide attention in the past decades.[1,2,3,4,5,6,7,8,9,10] With the development of science and technique, the target’s radar cross section becomes lower and lower, and the radar detection performance is affected. For the highly maneuvering target, i.e., with jerk motion, these above-mentioned methods will suffer from detection performance To overcome this problem, the generalized RFT (GRFT),[19] which completes the coherent integration via jointly searching along range cell, radial velocity, acceleration, and jerk directions, is proposed. To reduce the computational complexity, some detection methods based on nonlinear autocorrelation functions (AFs) are proposed These methods can be divided into two categories: the AFs constructed in the range frequency domain and slow time domain, respectively. Based on the consideration of improving the balance between the computational complexity and detection performance for the methods constructing the AFs in the slow time domain, a coherent detection method based on two-dimensional (2D) trilinear autocorrelation function (TAF) is proposed in this paper.
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