Cognitive Beacon Estimation of Unknown LEO Satellites Signals of Opportunity for PNT

A framework that could detect the presence of repetitive features in unknown signals is developed and experimentally demonstrated with non-terrestrial (NTN) sources, namely GPS and low Earth orbit (LEO) satellites. In modern communication systems, the existence of repetitive feature (i.e., the beacon) in the transmitted signals is inherited either implicitly; due to the transmitter’s source and channel coding, modulation, and multiplexing schemes; or explicitly, by broadcasting repetitive sequences for synchronization purposes. Upon detecting an unknown source, this framework, termed cognitive beacon detection and estimation, is capable of estimating the beacon, regardless of the adopted modulation scheme by the source. First, a model that is adequate to describe received signals from highly dynamic satellite channels is presented. The model parametrizes signals received from multiple unknown sources in terms of their time-varying carrier power, delay, Doppler, and user data. Second, a sequential beacon detection and estimation approach is developed, which is agnostic to the modulation scheme employed by the transmitter. The proposed cognitive framework allows for opportunistic exploitation of salient information embedded in the estimated beacon, such as beam, sector, and transmitter identification sequences. Third, the proposed framework is shown to converge almost surely to the correct beacon one at a time, until all sources are detected. Fourth, experimental results are presented demonstrating the efficacy of the developed cognitive framework in blindly detecting and estimating beacons of NTN sources, namely GPS and 5 LEO constellations: NOAA, Orbcomm, Iridium, Starlink, and OneWeb. These sources transmit in a diverse swath of modulation schemes: AM/FM, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</i>-PSK, SC-FDMA, and OFDM. Finally, experimental results are presented demonstrating the applicability of the developed framework in navigating a ground vehicle with multi-constellation LEO satellite signals. The pseudorange rate measurements produced by the framework to 2 Orbcomm, 1 Iridium, 4 Starlink, and 1 OneWeb were fused with altimeter measurements via an extended Kalman filter to estimate the vehicle’s nearly 1 km trajectory, achieving a three-dimensional position root mean squared error of 4.15 m.