Quantum Optimised Beam Allocation with a Radar Network for Multiple Target Tracking

Kurzfassung

Optimally allocating a limited number of radar beams to actively track multiple targets is a computationally intensive task. The quantum approximate optimisation algorithm, a method for efficiently finding near optimal solutions to combinatorial optimisation problems, was assessed in its ability to find good beam allocations. A simulation, including sensors, targets, and an extended Kalman filter, was created specifically for this work and was used in tandem with a simulated quantum environment to this end. After reformulating the problem, two small scale test cases were implemented. In both cases, the returned beam allocations were optimal in that they resulted in as many targets as possible being tracked to an acceptable level based on predetermined thresholds. In addition, a complexity analysis was performed which suggests that a quantum advantage may be possible for this problem if the quantum circuit parameters can be efficiently calculated. Based on these results, the quantum approximate optimisation algorithm is promising for the beam allocation problem.