Suboptimal Kalman filters for target tracking with navigation uncertainty in one dimension

Abstract

Abstract-The vast majority of literature on target tracking assumes that the position and orientation of the tracking sensor is stationary and/or known. However, for many applications the sensor is mounted on a moving vehicle, whose motion only can be estimated with a non-negligible uncertainty. In this paper, we suggest seven possible architectures for Kalman filtering in the simplest such scenario that we can construct: Assuming that both the ownship and a single target moves along a straight line according to linear kinematics. Some of the tracking filters are parameterized in the stationary world frame, while others are parameterized the body frame of the ownship. Also, some of the tracking filters take correlations between target state and ownship state into account, while others neglect such correlations. Simulations demonstrate that the suboptimal architectures may or may not reach similar performance as the optimal filter, depending on the process noise of the target and the performance measure chosen. Simulations of multitarget scenarios demonstrate that compensation of navigation uncertainty generally can reduce track-loss rates and OSPA distance.

Radar-based maritime collision avoidance using dynamic window

“…Given the performance of the Seapath navigation system, navigation uncertainty is of minor impact to the target tracking system, and will be neglected. This is supported by simulation studies in [23] and [3] which indicated that navigation uncertainty would have to be significantly higher to have noticeable impact. The vessel tracking and control system is implemented in the robot operating system (ROS) [19], and the vessel actuators are interfaced via a proprietary interface developed by Maritime Robotics.…”

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“…Sebelumnya beberapa peneliti telah menggunakan Kalman Filter pada kasus-kasus berbeda-beda seperti penurunan noise pada banyak sensor RFID secara bersamaan [5], verifikasi nilai sensor pada modul Zigbee [6] penentuan target dari suatu navigasi yang nilainya tidak menentu [7], memprediksi data pada jaringan WSN (Wireless Network Sensor) [8][9] [10]. Yang pengolahan datanya menggunakan bantuan software seperti Matlab yang artinya membutuhkan perangkat keras komputer dalam pengolahan datanya.…”

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“…Target tracking in the presence of navigation uncertainty has been studied for autonomous ships [6,31,32]. However, these articles have focused on a subset of the navigation space and used a radar as the tracking sensor.…”