With global coverage, high accuracy, and lightweight receivers, global navigation satellite system (GNSS) has been the major positioning solution for unmanned aerial vehicles (UAV). However, GNSS is prone to electromagnetic interference and malicious attacks such as jamming or spoofing due to its low signal-to-noise ratio (SNR). To ensure the continuity and safety of UAV operation, the use of redundant navigation systems is crucial. Phased array radio system (PARS) has proven its potential as a local navigation solution in the last few years. PARS is robust against malicious attacks due to a significantly higher SNR than GNSS together with directional and encrypted transmission. One of the challenges of the PARS-based navigation is the radio antenna at ground station, as its orientation needs to be determined precisely to obtain accurate navigation solution for unmanned vehicles. This paper presents an automatic calibration algorithm for the ground radio antenna orientation using a multiplicative extended Kalman filter (MEKF) based on GNSS and PARS measurements. The calibration algorithm was tested with data obtained from a field test using a fixed wing UAV and validated by a residual analysis comparing the PARS-and GNSS-based positioning.

<p>Global Navigation Satellite Systems (GNSS) have been the primary positioning solution for Unmanned Aerial Vehicles (UAVs) due to their worldwide coverage, high precision, and lightweight receivers. However, GNSS is prone to electromagnetic interference and malicious assaults, including jamming or spoofing because of its low signal-to-noise ratio (SNR). Using redundant navigation systems is essential to ensure the continuity and protection of UAV operations. In recent years, the phased array radio system (PARS) has established itself as a local navigation solution. PARS is robust towards malicious assaults because of a much higher SNR than GNSS regarding directed and encrypted transmission. An essential factor of PARS is that the orientation of the radio antenna at a ground station needs to be precisely determined to obtain the correct positioning of UAVs. This paper presents a method for extending a previously proposed calibration algorithm to estimate the ground antenna orientation with an inertial navigation system (INS) aided by redundant positioning sensors (GNSS, PARS, or barometer) using a multiplicative extended Kalman filter (MEKF) so that the calibration can be activated during flights whenever GNSS is available. In other words, the proposed navigation system is essentially an aided-INS that switches between two modes depending on the availability of GNSS: calibration and GNSS aiding mode when GNSS is available (Mode 1) and PARS and barometer aiding mode when GNSS is unavailable (Mode 2). Considering that the navigation system needs to include the effect of Earth's curvature for a long-distance flight, PARS horizontal measurement and the barometer measurement were treated independently, and the navigation equations were propagated in Earth Centred Earth Fixed (ECEF) frame. The independent treatment of barometer measurement, and the propagation in ECEF frame were also beneficial when using multiple ground antennas to have a common reference point and reference frame. The proposed method was validated using data (Inertial Measurement Unit (IMU), GNSS, PARS, Pixhawk autopilot (including barometer) measurements) collected during a field test. In the validation, GNSS was made available at the middle of the flight and the calibration mode was activated for 200s. The proposed navigation system successfully estimated the precise orientation of multiple ground antennas and the navigation solutions were verified using GNSS and Pixhawk autopilot solutions as ground truth.</p>

<p>Global Navigation Satellite Systems (GNSS) have been the primary positioning solution for Unmanned Aerial Vehicles (UAVs) due to their worldwide coverage, high precision, and lightweight receivers. However, GNSS is prone to electromagnetic interference and malicious assaults, including jamming or spoofing because of its low signal-to-noise ratio (SNR). Using redundant navigation systems is essential to ensure the continuity and protection of UAV operations. In recent years, the phased array radio system (PARS) has established itself as a local navigation solution. PARS is robust towards malicious assaults because of a much higher SNR than GNSS regarding directed and encrypted transmission. An essential factor of PARS is that the orientation of the radio antenna at a ground station needs to be precisely determined to obtain the correct positioning of UAVs. This paper presents a method for extending a previously proposed calibration algorithm to estimate the ground antenna orientation with an inertial navigation system (INS) aided by redundant positioning sensors (GNSS, PARS, or barometer) using a multiplicative extended Kalman filter (MEKF) so that the calibration can be activated during flights whenever GNSS is available. In other words, the proposed navigation system is essentially an aided-INS that switches between two modes depending on the availability of GNSS: calibration and GNSS aiding mode when GNSS is available (Mode 1) and PARS and barometer aiding mode when GNSS is unavailable (Mode 2). Considering that the navigation system needs to include the effect of Earth's curvature for a long-distance flight, PARS horizontal measurement and the barometer measurement were treated independently, and the navigation equations were propagated in Earth Centred Earth Fixed (ECEF) frame. The independent treatment of barometer measurement, and the propagation in ECEF frame were also beneficial when using multiple ground antennas to have a common reference point and reference frame. The proposed method was validated using data (Inertial Measurement Unit (IMU), GNSS, PARS, Pixhawk autopilot (including barometer) measurements) collected during a field test. In the validation, GNSS was made available at the middle of the flight and the calibration mode was activated for 200s. The proposed navigation system successfully estimated the precise orientation of multiple ground antennas and the navigation solutions were verified using GNSS and Pixhawk autopilot solutions as ground truth.</p>