Doppler effect on target tracking in wireless sensor networks

This paper presents a new detection algorithm and high speed/accuracy tracker for tracking ground targets in acoustic wireless sensor networks (WSNs). Our detection algorithm naturally accounts for the Doppler effect which is an important consideration for tracking higher-speed targets. This algorithm employs Kalman filtering (KF) with the weighted sensor position centroid being used as the target position measurement. The weighted centroid makes the tracker to be independent of the detection model and changes the tracker to be near optimal, at least within the detection parameters used in this study. Our approach contrasts with previous approaches that employ more sophisticated tracking algorithms with higher computational complexity and use a power law detection model. The power law detection model is valid only for low speed targets and is susceptible to mismatch with detection by the sensors in the field. Our tracking model also enables us to uniquely study various environmental effects on track accuracy, such as the Doppler effect, signal collision, signal delay, and different sampling time. Our WSN tracking model is shown to be highly accurate for a moving target in both linear and accelerated motions. The computing speed is estimated to be 50–100 times faster than the previous more sophisticated methods and track accuracy compares very favorably.