Estimation of Handheld Ground-Penetrating Radar Antenna Position with Pendulum-Model-Based Extended Kalman Filter

Abstract

Landmines and explosive remnants of war are a significant threat in tens of countries and other territories, causing the deaths or injuries of thousands of people every year, even long after military conflicts. Effective technical means of remote detecting, localizing, imaging, and identifying mines and other buried explosives are still sought and have a great potential utility. This paper considers a positioning system used as a supporting tool for a handheld ground penetrating radar. Accurate knowledge of the radar antenna position during terrain scanning is necessary to properly localize and visualize the shape of buried objects, which helps in their remote classification and makes demining safer. The positioning system proposed in this paper uses ultrawideband radios to measure the distances between stationary beacons and mobile units. The measurements are processed with an extended Kalman filter based on an innovative dynamics model, derived from the model of a pendulum motion. The results of simulations included in the paper prove that using the proposed pendulum dynamics model ensures a better accuracy than the accuracy obtainable with other typically used dynamics models. It is also demonstrated that our positioning system can estimate the radar antenna position with the accuracy of single centimeters which is required for appropriate imaging of buried objects with the ground penetrating radars.

Target Tracking Algorithm Based on Adaptive Strong Tracking Extended Kalman Filter

“…The Extended Kalman Filter (EKF) [26] stands out as one of the earliest and most successful applications in nonlinear filtering for tracking vehicle targets, exhibiting significant effectiveness [27][28][29]. Kaniewski [30] processed this using an Extended Kalman Filter based on an innovative dynamic model derived from a pendulum motion model. Zerdali [31] designed an Adaptive Fading Extended Kalman Filter (AFEKF) observer with improved magnetic flux, velocity, and load torque estimation for control applications that lack velocity sensors.…”