Optimal Signal Selection for Sensors

TL;DR

This paper introduces an integer linear programming approach combined with heuristics to optimize signal selection in sensors, balancing quality, energy, and computational constraints for radar and sonar applications.

Contribution

It presents a novel method for optimal signal selection using ILP and heuristics, considering multiple factors like quality, energy, and time, which improves sensing efficiency.

Findings

Effective signal mix synthesis based on multiple criteria

Improved computational performance with heuristic algorithms

Enhanced sensing quality with optimized signal selection

Abstract

The focus of this research is sensor applications including radar and sonar. Optimal sensing means achieving the best signal quality with the least time and energy cost, which allows processing more data. This paper presents novel work by using an integer linear programming "algorithm" to achieve optimal sensing by selecting the best possible number of signals of a type or a combination of multiple types of signals to ensure the best sensing quality considering all given constraints. A solution based on a heuristic algorithm is implemented to improve the computing time performance. What is novel in this solution is synthesis of an optimized signal mix using information such as but not limited to signal quality, energy and computing time.