Fusion of Inverse Synthetic Aperture Radar and Camera Images for Automotive Target Tracking

TL;DR

This paper presents a sensor fusion approach combining radar and vision data to improve target tracking and ISAR image quality for automotive applications, especially during turns.

Contribution

It introduces a novel low-complexity method using computer vision for target identification and fusion with radar data to enhance motion estimation and ISAR imaging.

Findings

Fusion improves target tracking accuracy during turns.

Sensor fusion enhances ISAR image resolution and quality.

Experimental results validate the effectiveness of the proposed method.

Abstract

Automotive targets undergoing turns in road junctions offer large synthetic apertures over short dwell times to automotive radars that can be exploited for obtaining fine cross-range resolution. Likewise, the wide bandwidths of the automotive radar signal yield high-range resolution profiles. Together, they are exploited for generating inverse synthetic aperture radar (ISAR) images that offer rich information regarding the target vehicle's size, shape, and trajectory which is useful for object recognition and classification. However, a key requirement for ISAR is translation motion compensation and estimation of the turning velocity of the target. State-of-the-art algorithms for motion compensation trade-off between computational complexity and accuracy. An alternative low complexity method is to use an additional sensor for tracking the target motion. In this work, we propose to exploit computer vision algorithms to identify the radar target object in the sensor field-of-view (FoV) with high accuracy. Further, we propose to track the target vehicle's motion through fusion of vision and radar data. Vision data facilitates the accurate estimation of the lateral position of the target which complements the radar capability of accurate estimation of range and radial velocity. Through simulations and experimental evaluations with a monocular camera and Texas Instrument millimeter wave radar we demonstrate the effectiveness of sensor fusion for accurate target tracking for translational motion compensation and the generation of high-quality ISAR images.