Design and verification of reduced redundancy ultrasonic MIMO arrays using simulated annealing & genetic algorithms

This paper considers methods and results on designing a reduced redundancy Multiple-Input, Multiple-Output (MIMO) ultrasonic sensor array to provide high-resolution, short-range sensing in front of a platform, while simultaneously reducing the amount of sensors required even further than a co-located MIMO array. The method proposed maximises the MIMO virtual aperture size rather than the conventional method of finding redundant physical elements to remove. This is done through adopting a Simulated Annealing and Genetic Algorithm for this problem, to optimise placement for a fixed and small number of sensor elements. The resulting array occupies less physical space than a conventional array of the same beamwidth, making it potentially attractive for small, mobile autonomous platforms. Analytical methods and simulation results are presented, and experimentally confirmed at the proof-of-concept level using a custom-built array. The experimental results verify that the proposed technique can reduce the amount of required sensor elements by 35% compared to a conventional MIMO array.