access icon openaccess Target separation detection and motion parameter estimation method based on time-varying autoregressive model

The authors report a target separation detection and motion parameter estimation method based on the time-varying autoregressive (TVAR) model. The TVAR model is used to extract the instantaneous Doppler frequencies of multiple targets or scattering points in a same radar range cell, and the motion parameters are estimated based on the Doppler frequencies at every pulse time in a radar frame. In particular, for coherent multipulse echo signal, the TVAR model is first utilised to extract multiple instantaneous Doppler frequencies at each pulse time, thus forming a Doppler frequency matrix. Second, the Doppler tracking and polynomial fitting methods are utilised to estimate the radial velocity and acceleration based on the Doppler frequency matrix. Finally, the target separation detection is achieved by acquiring and validating multiple Doppler frequency components in the same range cell. Simulations and verifications are carried out, and the results show that the proposed method is effective for target separation detection and precision motion parameter estimation, which could be of great value radar target detection, tracking, and automatic target recognition.

Inspec keywords: radar resolution; radar imaging; target tracking; object detection; radar signal processing; filtering theory; parameter estimation; autoregressive processes; radar detection; radar tracking; radar target recognition; Doppler radar

Other keywords: radar range cell; great value radar target detection; automatic target recognition; Doppler tracking; motion parameters; target separation detection; pulse time; acquiring validating multiple Doppler frequency components; multiple targets; TVAR model; precision motion parameter estimation; Doppler frequency matrix; multiple instantaneous Doppler frequencies; time-varying autoregressive model; motion parameter estimation method

Subjects: Other topics in statistics; Other topics in statistics; Radar equipment, systems and applications; Optical, image and video signal processing; Interpolation and function approximation (numerical analysis); Signal processing and detection; Computer vision and image processing techniques; Filtering methods in signal processing

References

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