A Hybrid Data Storage Method for Pulse-to-Pulse Optimizations

Abstract

Due to increasing congestion in the radar frequencies due to reallocations, the pressure upon radar systems to avoid interference through dynamically changing operating frequency has intensified. Many modern radar systems (often called “cognitive radar” systems) often have the ability to sense and avoid interference. Through the use of reconfigurable transmitter circuitry, the front end can be quickly reconfigured following a change in frequency to maximize output power and, hence, detection range. With the implementation of a fast, plasma-switch impedance tuner paired with an efficient circuit optimization, the ability to change tuner setting within a single radar pulse repetition interval (PRI) has been previously demonstrated. To carry out impedance-tuning optimization measurements for each PRI, an efficient data storage and lookup method is needed. In this article, we demonstrate how hybrid storage with a hash table can be used with an efficient, cache replacement algorithm on a software-defined radio (SDR) platform to enable continuous operation with pulse-to-pulse optimization. This data storage approach minimizes overhead in storage of circuit optimization settings, allowing faster optimization of the circuit to maximize output power. By maximizing output power quickly, it is expected that the radar will experience better signal-to-interference-plus-noise ratio and accurate detection of targets at greater ranges.