Ground Maneuvering Target Detection and Motion Parameter Estimation Method Based on RFRT-SLVD in Airborne Radar...

Area of Science:

• Radar signal processing
• Target detection and tracking
• Estimation theory

Background:

• Airborne radar systems face challenges in detecting and estimating motion parameters of ground maneuvering targets.
• Complex target motion, including velocity, acceleration, and jerk, causes range migrations (RMs) and Doppler frequency migrations (DFMs).
• These migrations degrade radar performance, limiting reliable detection and precise parameter estimation.

Purpose of the Study:

• To propose a new method, RFRT-SLVD, for detecting and estimating motion parameters of ground maneuvering targets for airborne radar.
• To address the limitations imposed by range and Doppler frequency migrations on radar performance.
• To improve the accuracy and reliability of maneuvering target detection and parameter estimation.

Main Methods:

• A novel detection and motion parameter estimation method, RFRT-SLVD, is proposed, combining range frequency reversal transform (RFRT) and searching Lv's distribution (SLVD).
• The method considers third-order range migration (TRM) and quadratic Doppler frequency migration (QDFM).
• RMs are eliminated using RFRT, and QDFM is compensated using a phase compensation function (PCF) related to jerk, followed by LVD for residual DFM removal.

Main Results:

• The RFRT-SLVD method effectively eliminates RMs and compensates for QDFMs, enabling signal energy accumulation.
• It allows for direct compensation of RMs without prior target knowledge and avoids the blind speed sidelobe (BSSL) effect.
• The method demonstrates a balanced trade-off between parameter estimation performance and computational efficiency, validated through numerical analyses and experiments.

Conclusions:

• The proposed RFRT-SLVD method offers a robust solution for detecting and estimating motion parameters of ground maneuvering targets in airborne radar systems.
• It significantly improves detection capability and parameter estimation accuracy, even in scenarios with Doppler ambiguity.
• The method shows applicability in multi-target scenarios and provides a computationally efficient alternative to existing algorithms.