Branch-and-Bound Method for Just-in-Time Optimization of Radar Search Patterns
This work addresses radar search pattern optimization for electronic phased-array radar systems, which is an incremental improvement in domain-specific real-time applications.
The paper tackled the problem of optimizing radar search patterns for electronic phased-array radars by approximating it as a set cover problem to minimize time-budget under constraints like range and detection probability, using a Branch-and-Bound method to produce just-in-time solutions.
Electronic phased-array radars offer new possibilities for radar search pattern optimization by using bi-dimensional beam-forming and beam-steering. Radar search pattern optimization can be approximated as a set cover problem and solved using integer programming, while accounting for localized clutter and terrain masks in detection constraints. We present a set cover problem approximation for time-budget minimization of radar search patterns, under constraints of range, detection probability and direction-specific scan update rates. Branch\&Bound is a classical optimization procedure for solving combinatorial problems. It is known mainly as an exact algorithm, but features interesting characteristics, making it particularly fit for solving optimization problems in real-time applications and producing just-in-time solutions.