<p>Global Navigation Satellite System (GNSS) reflected signals have been used to detect moving targets through long-time integration processing. However, mismatches arise between the target’s actual motion and the assumed motion model over a long integration time, degrading detection performance. To address this problem, this paper proposes an improved Track-before-Detect (TbD) method characterized by a two-stage architecture. In the first stage, current Long-Time Hybrid Integration (LTHI) techniques are employed to correct the range and Doppler migrations caused by the target’s motion, thereby concentrating the target energy within an individual scan duration. In the second stage, plot lists extracted from multiple scans are recursively processed to further accumulate target energy by using the target’s kinematic constraints across different scans. Finally, target energy is enhanced sufficiently for reliable detection, while also enabling the acquisition of the target’s motion parameters over all scans. Compared to the existing Dynamic Programming (DP)-TbD method, the proposed method can exploit the characteristics of the stack of integrated range and Doppler maps produced by the LTHI techniques to improve algorithm execution efficiency without sacrificing detection performance and parameter estimation accuracy. The results from the simulations and field trials confirm the effectiveness of the proposed method in detecting maneuvering and non-maneuvering targets. Meanwhile, the proposed method achieves detection performance and motion parameter estimation errors comparable to the existing DP-TbD method, while significantly lowering the computational time.</p>

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An improved track-before-detect method for moving target detection using GNSS reflected signals

  • Zhenyu He,
  • Yi Mao,
  • Yang Yang,
  • Wu Chen

摘要

Global Navigation Satellite System (GNSS) reflected signals have been used to detect moving targets through long-time integration processing. However, mismatches arise between the target’s actual motion and the assumed motion model over a long integration time, degrading detection performance. To address this problem, this paper proposes an improved Track-before-Detect (TbD) method characterized by a two-stage architecture. In the first stage, current Long-Time Hybrid Integration (LTHI) techniques are employed to correct the range and Doppler migrations caused by the target’s motion, thereby concentrating the target energy within an individual scan duration. In the second stage, plot lists extracted from multiple scans are recursively processed to further accumulate target energy by using the target’s kinematic constraints across different scans. Finally, target energy is enhanced sufficiently for reliable detection, while also enabling the acquisition of the target’s motion parameters over all scans. Compared to the existing Dynamic Programming (DP)-TbD method, the proposed method can exploit the characteristics of the stack of integrated range and Doppler maps produced by the LTHI techniques to improve algorithm execution efficiency without sacrificing detection performance and parameter estimation accuracy. The results from the simulations and field trials confirm the effectiveness of the proposed method in detecting maneuvering and non-maneuvering targets. Meanwhile, the proposed method achieves detection performance and motion parameter estimation errors comparable to the existing DP-TbD method, while significantly lowering the computational time.