Artificial Intelligence Meets Radar Resource Management Lit Review

Hashmi, Akbar, Adve, Moo, Ding Bottom Line Up Front Very dense, even for a lit review. Well structured, and will be useful as a reference once I start digging into a problem. Only obvious extension I can think of is looking for adjacent problems in other fields. I know bin packing and estimating state from measurements isn’t unique to radars, would be nifty to see what is going on outside of the ECE department....

January 30, 2023 · 4 min · 724 words · Amos

A Modified Reinforcement Q Learning Method for Multi Function Phased Array Radar Beam Scheduling

Kosuru, Qu, Ding, Moo. Bottom Line Up Front RL agent is forced to pick one of 4 schedulers. Usually hones in on the best one. Summary Introduction Radars can have many tasks. Tasks have priority $p$, times $t_{start}$,$t_{dwell}$. Windows have a length $L$. Time frame lasts $t_{total}$. Radar resource management “RRM” tries to maximize utilization of $L$ by dropping some tasks during overloading situations. Branch and Bound method is great but computationally expensive....

January 29, 2023 · 2 min · 396 words · Amos

Dual Side Scheduling for Radar Resource Management

Bottom Line Up Front Acronyms MFR: multi-function radar RRM: radar resource management EST: earliest-start-time (scheduling method) ED: earliest-deadline (secheduling method) DSS: dual side scheduling NCT: nearest closer time RSST: Random shifted start time Summary Instead of jamming tasks left, toss out some random points and scrunch them together about them. Fast enough to calculate, drop fewer and cost’s less after checking a bunch for one that costs less. Intro Phased array radars have multiple functions, which need different tasks completed....

January 28, 2023 · 3 min · 507 words · Amos