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.

Exploiting cellular long-term evolution (LTE) downlink signals for navigation purposes is considered. First, the transmitted LTE signal model is presented and relevant positioning and timing information that can be extracted from these signals are identified. Second, a software-defined receiver (SDR) that is capable of acquiring, tracking, and producing pseudoranges from LTE signals is designed. Third, a threshold-based approach for detecting the first peak of the channel impulse response is proposed in which the threshold adapts to the environmental noise level. This method is demonstrated to be robust against noise and interference in the environment. Fourth, an approach for estimating pseudoranges of multiple base stations by tracking only one base station is proposed. Fifth, a navigation framework based on an extended Kalman filter (EKF) is proposed to produce the navigation solution using the pseudorange measurements obtained by the proposed SDR. Finally, the proposed SDR is evaluated experimentally on an unmanned aerial vehicle (UAV) and a ground vehicle. The root mean squared-error (RMSE) between the GPS navigation solution and LTE signals from 3 base stations produced by the proposed SDR for the UAV is shown to be 8.15 m with a standard deviation of 2.83 m. The RMSE between the GPS navigation solution and LTE signals from 6 base stations in a severe multipath environment for the ground vehicle is shown to be 5.80 m with a standard deviation of 3.02 m.

I am not afraid of the GPS jammer, as long as there are ambient signals of opportunity (SOPs) to exploit in the environment. In environments where GPS signals are challenged (e.g., indoors and deep urban canyons) or denied (e.g., under jamming and spoofing attacks), SOPs could serve as an alternative positioning, navigation, and timing (PNT) source to GPS, and more generally, to global navigation satellite systems (GNSS). This article presents a radio simultaneous localization and mapping (radio SLAM) approach that enables the exploitation of SOPs for resilient and accurate PNT. Radio SLAM estimates the states of the navigator-mounted receiver simultaneously with the SOPs’ states. Radio SLAM could produce an SOP-derived navigation solution in a standalone fashion or by fusing SOPs with sensors [e.g., inertial measurement unit (IMU), lidar, etc.], digital maps, and/or other signals (e.g., GNSS). This article presents the first published experimental results evaluating the efficacy of radio SLAM in a real GPS-denied environment. These experiments took place at Edwards Air Force Base, California, USA, during which GPS was intentionally jammed with jamming-to-signal ratio as high as 90 dB. This article evaluates the timing of two cellular long-term evolution (LTE) SOPs located in the jammed environment, showing timing stability over 95 min of GPS jamming. Moreover, the article presents navigation results showcasing a ground vehicle traversing a trajectory of about 5 km in 180 s in the GPS-jammed environment. The vehicle's GPS-IMU system drifted from the vehicle's ground truth trajectory, resulting in a position root mean-squared error (RMSE) of 238 m. In contrast, the radio SLAM approach with a single cellular LTE SOP whose position was poorly known (an initial uncertainty on the order of several kilometers) achieved a position RMSE of 32 m.

A method for achieving lane-level localization in global navigation satellite system (GNSS)-challenged environments is presented. The proposed method uses the pseudoranges drawn from unknown ambient cellular towers as an exclusive aiding source for a vehicle-mounted light detection and ranging (lidar) sensor. The following scenario is considered. A vehicle aiding its lidar with GNSS signals enters an environment where these signals become unusable. The vehicle is equipped with a receiver capable of producing pseudoranges to unknown cellular towers in its environment. These pseudoranges are fused through an extended Kalman filter (EKF) to aid the lidar odometry, while estimating the vehicle's own state (three-dimensional position and orientation) simultaneously with the position of the cellular towers and the difference between the receiver's and cellular towers' clock error states (bias and drift). The proposed method is computationally efficient and is demonstrated to achieve lane-level accuracy in different environments. Simulation and experimental results with the proposed method are presented illustrating a close match between the vehicle's true trajectory and that estimated using the cellular-aided lidar odometry over a 1 Km trajectory. A 60% reduction in localization error is obtained over the lidar odometry-only approach.

A navigation framework with carrier phase differential measurements from megaconstellation low Earth orbit (LEO) satellite signals is developed. The measurement errors due to ephemeris errors and ionospheric and tropospheric delays are derived and the statistics of the dilution of precision is characterized. Moreover, the joint probability density function of the megaconstellation LEO satellites' azimuth and elevation angles is derived to (i) enable performance characterization of navigation frameworks with LEO satellites in computationally efficient way and (ii) facilitate parameter design, namely, the differential baseline, to meet desired performance requirements. The Starlink constellation is used as a specific LEO megaconstellation example to demonstrate the developed carrier phase differential LEO (CD-LEO) navigation framework. Simulation results are presented demonstrating the efficacy of the proposed CD-LEO framework for an unmanned aerial vehicle (UAV) navigating for 15.1 km in 300 seconds, while using signals from 44 Starlink satellites, achieving a three-dimensional (3-D) position root mean squared error (RMSE) of 2.2 m and a 2-D RMSE of 32.4 cm. Experimental results are presented showing UAV navigating for 2.28 km in 2 minutes over Aliso Viejo, California, USA, using exclusively signals from only two Orbcomm LEO satellites, achieving an unprecedented position RMSE of 14.8 m.