Sensor scheduling for ground maneuvering target tracking in presence of detection blind zone

Continuous and stable tracking of the ground maneuvering target is a challenging problem due to the complex terrain and high clutter. A collaborative tracking method of the multisensor network is presented for the ground maneuvering target in the presence of the detection blind zone(DBZ). First, the sensor scheduling process is modeled within the partially observable Markov decision process(POMDP) framework. To evaluate the target tracking accuracy of the sensor, the Fisher information is applied to constructing the reward function. The key of the proposed scheduling method is forecasting and early decisionmaking. Thus, an approximate method based on unscented sampling is presented to estimate the target state and the multi-step scheduling reward over the prediction time horizon. Moreover, the problem is converted into a nonlinear optimization problem, and a fast search algorithm is given to solve the sensor scheduling scheme quickly. Simulation results demonstrate the proposed nonmyopic scheduling method(Non-MSM) has a better target tracking accuracy compared with traditional methods.

Method of target tracking with Doppler blind zone constraint

Doppler blind zone （DBZ） has a bad influence on the airborne early warning radar, although it has good detection performance for low altitude targets with pulse Doppler （PD） technology. In target tracking, the blind zone can cause target tracking breakage easily. In order to solve this problem, a parallel particle filter （PF） algorithm based on multi-hypothesis motion models （MHMMs） is proposed. The algorithm produces multiple possible target motion models according to the DBZ constraint. Particles are updated with the constraint in each motion model. Once the first measurement from the target which reappears from DBZ falls into the particle cloud formed by any model, the measurementtrack association succeeds and track breakage is avoided. The simulation results show that on the condition of different DBZ ranges, a high association ratio can be got for targets with different maneuverability levels, which accordingly improves the tracking quality.

Design and implementation of a visual monitoring system to ensure safety in the water surrounding a container vessel

Container vessels navigate among the world＇s ports, frequently passing through narrow and congested waters. Due to the many layers of containers on a container vessel＇s decks, it is difficult for the crew to be aware of all fishing vessels and other obstacles in a container vessel＇s radar observation blind zone. This greatly increases the risk of collisions and other accidents. Given such great challenges to safe navigation and safety management with container vessels, their security risks are severe. An effective visual monitoring system can improve the safety of the water area surrounding container vessel by eliminating a vessel＇s observation blind zone, providing an effective safety measure for vessels navigating fishing zones and other troublesome areas. The system has other functions, such as accident recording, ship security, and monitoring of loading and unloading operations, thus ensuring the ship operates safely. Six months＇ trial operation showed that the system facilitates safe navigation of container vessels.

A multi-sensor-system cooperative scheduling method for ground area detection and target tracking

A multi-sensor-system cooperative scheduling method for multi-task collaboration is proposed in this paper.We studied the method for application in ground area detection and target tracking.The aim of sensor scheduling is to select the optimal sensors to complete the assigned combat tasks and obtain the best combat benefits.First,an area detection model was built,and the method of calculating the detection risk was proposed to quantify the detection benefits in scheduling.Then,combining the information on road constraints and the Doppler blind zone,a ground target tracking model was established,in which the posterior Carmér-Rao lower bound was applied to evaluate future tracking accuracy.Finally,an objective function was developed which considers the requirements of detection,tracking,and energy consumption control.By solving the objective function,the optimal sensor-scheduling scheme can be obtained.Simulation results showed that the proposed sensor-scheduling method can select suitable sensors to complete the required combat tasks,and provide good performance in terms of area detection,target tracking,and energy consumption control.