GNSS Interference in Unmanned Aerial Systems

This paper discusses interference issues in Unmanned Aerial Systems (UAS) and addresses the benefit of advanced monitoring and mitigation capabilities built into the GNSS receiver module. First the paper discusses experimental results of interference of UAV electronics into the GNSS sensor. The analysis is based on a specific RF signal monitoring technique built into the receiver module. Several ways to mitigate this self-interference are discussed. Furthermore the impact of various types of jammers on GNSS reception is experimentally analyzed. A recorded UAV flight is recreated with an RF constellation simulator, adding interference from various jammer types. The interference level is controlled according to electromagnetic propagation laws, taking into account the attitude of the UAV and its antenna radiation pattern. In this way we evaluated the performance of several receivers under jamming exposure, proving effectiveness of advanced interference mitigation. INTRODUCTION The GNSS sensor is a vital part in the large majority of unmanned aerial systems. It is commonly used to guide UAVs, making sure it follows the pre-defined flight path. Most professional UAVs operate autonomously. If the GNSS position is lost, the UAV will still be stabilized by its inertial sensors, but it will be unable to navigate towards its landing spot without intervention of a human operator. Often this would simply lead to loss of the UAV and its payload. The precision of the navigation solution is also important. For guidance this mainly holds for complex flight phases such as landing. Landing has demanding precision requirements. For fixed-wing UAVs, altitude inaccuracies of 1 m lead to about 10-m inaccuracy on the landing spot. Rotorcrafts are typically supposed to operate from welldefined spots, and meter-level navigation inaccuracies could lead to collisions with surrounding objects. The most common application for professional UAS is aerial mapping. Camera images are used to create a precise three dimensional model of an area, e.g. to monitor progress of the works in a mining pit or construction yard. Aerial mapping used to require a large number of manually-surveyed reference points on the ground, but there is a trend to eliminate these by moving the high precision positioning to the UAV. The GNSS sensor is synchronized with the camera shutter and cm-accurate geotags are created for each picture. High precision navigation requires phase based techniques. Most aerial mapping UAS use dual frequency (L1/L2) RTK receivers, as these have the ability to instantaneously provide a reliable cm-accurate position. Phase based positioning techniques require good signal availability and quality (C/No). Ensuring this in interference rich environment UAVs typically operate is a challenging task. The article is organized as follows: first we explain the architecture of the receiver used in the experiments. Next we discuss the problem and mitigation of self-interference. This is followed by a section on alien interference and a description of the influence of the geometry on the susceptibility. Finally, we present a case study of a simulated flight in the presence of different types of jammers and the effect they have on different types of receivers. RECEIVER ARCHITECTURE The analysis and tests discussed in this paper were made with the Septentrio’s AsteRx4 multi-frequency RTK/PPP receiver modules. This module supports all L1, L2 and E5/L5 signals from all constellations. Figure 1: Septentrio’s AsteRx4 receiver architecture This module is specifically designed for operation in harsh interference environments. The antenna signal is downconverted in a multi-channel two stage heterodyning frontend with sharp surface acoustic wave (SAW) filters to reject out-of-band interferers. The output signals are quantized by multi-bit ADCs. The receiver has a built-in capability to log a batch of raw RF signal. The logged samples can be used to detect and study signal anomalies, both in the time and frequency domain. The digitized GNSS bands are automatically cleaned from interference by multiple adaptive band-stop filters. Their stop-band bandwidth is adjusted automatically between a notch of a few kHz to a MHz-wide rejection, depending on the nature of the interference. The notch filters are complemented by an adaptive filter capable to reject more complex types of interference such as chirp jammers and frequency hopping interference like DME/TACAN [1]. The receiver also supports regular blanking [2, 3]. The sub-bands (GPS L1, L2, L5; GLONASS L1, L2; GALILEO E1, E5; BeiDou B1, B2) are extracted by subband filters, which isolate them from residual interference in adjacent GNSS bands. The recovered signals are further processed in a large matrix of tracking channels, capable to simultaneously process all satellite signals in all received bands, even after the emerging constellations (e.g. GALILEO) will be completed. The collected measurements enter the navigation processor, which computes a high-rate RTK, PPP or SBAS-aided position depending on the corrections provided to the receiver. The measurements can also be logged onto flash memory (SD/eMMC) for replay or post processing, along with the time tag of event-triggers. The latter is particularly interesting for aerial geo-tagging applications, as it eliminates the need to uplink differential corrections to the UAV during the complete flight. RTK accuracy can then be achieved by post-processing of the logged GNSS measurements and photographs meta-data be edited a posteriori.