Finite Impulse Response Filter-Based Track Formation for Preceding Vehicle Tracking Using Automotive Radars

Area of Science:

• Automotive engineering
• Sensor technology
• Signal processing

Background:

• Automotive radars are crucial for preceding vehicle tracking.
• Cluttered road conditions lead to false radar measurements, hindering tracking accuracy.
• Robust automotive radar systems are needed to overcome these limitations.

Purpose of the Study:

• To propose a novel track formation algorithm for initializing preceding vehicle tracking in automotive radar systems.
• To enhance the robustness of automotive radar systems against false measurements in cluttered environments.

Main Methods:

• Development of a novel track formation algorithm based on finite impulse response (FIR) filtering.
• Evaluation of the algorithm's performance using extensive simulations under real-world driving conditions.

Main Results:

• The proposed algorithm demonstrated significantly higher accuracy in highly cluttered environments compared to conventional methods.
• The algorithm effectively initializes preceding vehicle tracking, even with numerous false measurements.
• Simulations confirmed the algorithm's excellent performance under realistic scenarios.

Conclusions:

• The novel FIR filter-based track formation algorithm provides a robust solution for preceding vehicle tracking in automotive radar systems.
• This advancement contributes to improved safety and reliability of autonomous driving features.
• The proposed method offers superior performance in challenging, cluttered road conditions.