This letter shows the first carrier phase tracking and positioning results with Starlink’s low earth orbit (LEO) satellite signals. An adaptive Kalman filter based algorithm for tracking the beat carrier phase from the unknown Starlink signals is proposed. Experimental results show carrier phase tracking of six Starlink satellites and a horizontal positioning error of 7.7 m with known receiver altitude.

This letter shows the first acquisition, Doppler tracking, and positioning results with Starlink's low Earth orbit satellite signals. A generalized-likelihood-ratio-based test is proposed to acquire Starlink's downlink signals. A Kalman-filter-based algorithm for tracking the Doppler frequency from the unknown Starlink signals is developed. Experimental results show Doppler tracking of six Starlink satellites, achieving a horizontal positioning error of 10 m.

A comprehensive approach for opportunistic navigation with fifth-generation (5G) cellular signals that exploits the downlink channel is developed. The structure of possible 5G reference signals that can be exploited is presented. Then, a software-defined receiver (SDR) to extract navigation observables from cellular 5G signals is proposed. The statistics of the code phase error in a multipath-free environment and in the presence of multipath are derived, which are subsequently used to analyze the statistics of the position estimation error with different simulated channel models. Finally, experimental results are conducted to evaluate the ranging performance of the proposed SDR with real 5G signals. After removing the effect of the clock bias and drift from the estimated pseudorange, the ranging error standard deviation is shown to be 1.19 m.

Global navigation satellite systems (GNSSs) have been the prevalent positioning, navigation, and timing technology over the past few decades. However, GNSS signals suffer from four main limitations.

Mitigating multipath of cellular long‐term evolution (LTE) signals for robust positioning in urban environments is considered. A computationally efficient receiver, which uses a phase‐locked loop (PLL)–aided delay‐locked loop (DLL) to track the received LTE signals, is presented. The PLL‐aided DLL uses orthogonal frequency division multiplexing (OFDM)–based discriminator functions to estimate and track the time‐of‐arrival. The code phase and carrier phase performances in an additive white Gaussian noise (AWGN) channel are evaluated numerically. The effects of multipath on the code phase and carrier phase are analyzed, demonstrating robust multipath mitigation for high transmission LTE bandwidths. The average of the DLL discriminator functions over multiple LTE symbols is presented to reduce the pseudorange error. The proposed receiver is evaluated on a ground vehicle in an urban environment. Experimental results show a root mean square error (RMSE) of 3.17 m, a standard deviation of 1.06 m, and a maximum error of 6.58 m between the proposed LTE receiver and the GPS navigation solution over a 1.44 km trajectory. The accuracy of the obtained pseudoranges with the proposed receiver is compared against two algorithms: estimation of signal parameters by rotational invariance techniques (ESPRIT) and EKAT (ESPRIT and Kalman filter).

A framework to exploit megaconstellation low Earth orbit (LEO) satellite signals of opportunity for navigation is developed. This framework, termed simultaneous tracking and navigation (STAN), estimates the navigating vehicle's states simultaneously with the states of orbiting LEO satellites. STAN employs a cognitive receiver that exploits megaconstellation LEO satellite downlink signals to produce navigation observables: pseudorange, Doppler, and/or carrier phase. These observables are fused through an extended Kalman filter (EKF) to aid the vehicle's inertial navigation system (INS) in a tightly coupled fashion. Simulation results are presented demonstrating the efficacy of the STAN framework. These simulations assumed the aerial vehicle to be equipped with an altimeter and a tactical-grade inertial measurement unit (IMU), navigating for 15.43 km in 300 seconds, in which GNSS signals were only available for the first 60 seconds. It is demonstrated that the final three-dimensional (3-D) position error and position root mean squared error (RMSE) of a typical tightly-coupled GNSS-aided INS grows to 1,536 m and 897 m, respectively. In contrast, the STAN framework with 77 LEO satellites (resembling Orbcomm, Iridium NEXT, and Starlink constellations) achieved a final 3-D position error and position RMSE of 15.2 m and 7.3 m, respectively with pseudorange measurements, and 37.1 m and 10.6 m, respectively with Doppler measurements. In addition, the first multi-constellation LEO navigation experimental results of their kind are presented of a ground vehicle traversing 4.15 km in 150 seconds, in which GNSS signals were only available for the first 80 seconds. It is shown that while the final 3-D position error of the vehicle's GNSS-aided INS with a tactical-grade IMU and an altimeter grew to 472.7 m and the 3-D position RMSE grew to 118.5 m; in contrast, the final 3-D position error and position RMSE of the STAN framework with received signals from 2 Orbcomm, 1 Iridium NEXT, and 3 Starlink LEO satellites were 27.1 m and 18.4 m, respectively.