Compression Design for Efficient Information Sharing in a Network of Radio Frequency Sensors

There is a desire to maximise efficiency when sharing positioning, navigation, and timing (PNT) information captured by low size, weight, power, and cost (SWAP-C) radio frequency (RF) sensors in distributed sensor networks. Such information can be used to position the sensors or RF sources in both civilian and military applications. We propose a novel framework for improving efficiency when sharing PNT information in a network of sensors receiving radar waveforms in an urban, contested electromagnetic environment. We show that informed, at-edge compression strategies that prioritise the transmission of PNT information in the presence of interferers can be obtained using information theory, and that these techniques outperform the uninformed strategies typically utilised during compressed sensing. Furthermore, we exhibit the flexibility of these strategies when facilitating trade-offs between different types of PNT information. We demonstrate the impact of compression level and signal-to-noise ratio on PNT activities and we confirm that, for a given network bandwidth, sensing gains can be achieved by combining compressed measurements from multiple sensors.