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Hybrid Interacting Multiple Model Filtering for Improving the Reliability of Radar-Based Forward Collision Warning
1Department of Electrical Engineering, Wonkwang University, 460 Iksan-Daero, Iksan 54538, Korea.
Sensors (Basel, Switzerland)
|February 15, 2022
Summary
This study introduces a new algorithm for automotive forward collision warning (FCW) systems. By combining interacting multiple model probabilistic data association (IMM-PDA) and finite impulse response (FIR) filters, it enhances the reliability of preceding vehicle tracking.
Area of Science:
- Automotive Engineering
- Sensor Technology
- Signal Processing
Background:
- Automotive forward collision warning (FCW) systems are crucial for vehicle safety.
- Accurate estimation of preceding vehicle position and velocity is essential for FCW reliability.
- Radar sensors are widely used in automotive applications for object detection.
Purpose of the Study:
- To propose a novel estimation algorithm for reliable preceding vehicle tracking in FCW systems.
- To address the divergence issue of the interacting multiple model probabilistic data association (IMM-PDA) filter in cluttered environments.
- To improve the overall performance and reliability of automotive radar-based FCW systems.
Main Methods:
- A hybrid algorithm combining the interacting multiple model probabilistic data association (IMM-PDA) filter and the finite impulse response (FIR) filter was developed.
- The IMM-PDA filter, known for tracking maneuvering targets, was augmented with an FIR filter to reset and recover from potential divergence caused by modeling errors.
- The proposed algorithm was evaluated through simulations of preceding vehicle tracking using automotive radar data.
Main Results:
- The novel hybrid IMM-PDA and FIR filter algorithm demonstrated improved reliability in preceding vehicle estimation.
- The FIR filter effectively mitigated the divergence problems of the IMM-PDA filter, ensuring consistent tracking performance.
- Simulations confirmed the enhanced accuracy and robustness of the proposed algorithm for automotive radar applications.
Conclusions:
- The proposed hybrid IMM-PDA-FIR algorithm offers a reliable solution for preceding vehicle estimation in automotive FCW systems.
- This approach enhances the robustness of target tracking by overcoming the limitations of traditional IMM-PDA filters.
- The findings contribute to the advancement of safer and more dependable automotive safety systems.
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