Finding optimal Pulse Repetion Intervals with Many-objective Evolutionary Algorithms

TL;DR

This paper applies many-objective evolutionary algorithms to optimize Pulse Repetition Intervals in Pulsed-Doppler radar, balancing range and Doppler ambiguities, and compares different algorithms to establish a baseline for radar design optimization.

Contribution

It introduces a real-world multi-objective optimization problem for radar parameter tuning and evaluates various evolutionary algorithms to identify Pareto optimal solutions.

Findings

Established a reference set of Pareto optimal points.

Compared multiple evolutionary algorithms for black-box optimization.

Provided insights for radar designers on optimal Pulse Repetition Intervals.

Abstract

In this paper we consider the problem of finding Pulse Repetition Intervals allowing the best compromises mitigating range and Doppler ambiguities in a Pulsed-Doppler radar system. We revisit a problem that was proposed to the Evolutionary Computation community as a real-world case to test Many-objective Optimization algorithms. We use it as a baseline to compare several Evolutionary Algorithms for black-box optimization with different metrics. Resulting data is aggregated to build a reference set of Pareto optimal points and is the starting point for further analysis and operational use by the radar designer.