UAV Navigation with Carrier Phase Cellular CDMA Signals

This video presents an experimental demonstration of a UAV navigating exclusively with cellular CDMA signals using precise carrier phase measurements. The UAV was listening to three cellular CDMA base stations. The received cellular signals were processed with the Multichannel Adaptive TRansciever Information eXtractor (MATRIX) software-defined receiver (SDR) developed by the ASPIN Laboratory. The cellular CDMA navigation solution is compared to the solution obtained from the UAV's on-board navigation system (the A3 flight controller), which consists of a GPS receiver, an IMU, a barometer, and a magnetometer. The cellular CDMA navigation solution over more than 5 minutes of flight time was within 1.2 m from the GPS navigation solution.

 
Collaborative Cellular-Aided Inertial Navigation 

 

Distributed Cellular-Aided Inertial Navigation with Intermittent Communication

This video presents an experimental demonstration of a distributed signal of opportunity (SOP)-aided inertial navigation system (INS) framework. This framework enables multiple unmanned aerial vehicles (UAVs) to aid their on-board INSs by communicating INS information and mutual pseudorange observables extracted from cellular transmitters.  The pseudoranges were obtained using the Multichannel Adaptive TRansceiver Information eXtractor (MATRIX) LTE SDR developed in the ASPIN Laboratory. This framework is studied in a lossy wireless communication channel with a probability of packet drop p. While GPS is available, the UAVs use their INSs aided by GPS and cellular signals to navigate, while simultaneously mapping the cellular transmitters. When GPS signals become unavailable, the UAVs navigate exclusively with their INSs aided by cellular pseudoranges, while simultaneously mapping the cellular transmitters (i.e., performing collaborative radio SLAM). Results demonstrate that even with a high probability of packet drop (p = 0.7), the exploitation of free ambient cellular SOPs in the environment significantly reduces INS errors in the absence of GPS. The results are compared with a perfect communication assumption (p = 0).

 
 
 
 
Collaborative Cellular-Aided Inertial Navigation

 

Ground Vehicle Navigation with LTE Signals in a Multipath Environment

This video presents ground vehicle navigation using long-term evolution (LTE) signals in an urban multipath environment: downtown Riverside, California. These results were obtained using the Multichannel Adaptive TRansceiver Information eXtractor (MATRIX) LTE SDR developed in the ASPIN Laboratory. This computationally efficient receiver exploits the cell-specific reference signal (CRS) to estimate the time-of-arrival. The high transmission bandwidth of the CRS (up to 20 MHz) makes it robust in a multipath environment. Although the received LTE signals experience more multipath than GPS signals due to the low elevation angles at which signals are received, the results show meter-level accuracy in navigation with the MATRIX LTE SDR compared to the GPS navigation solution.

 
 
Collaborative Cellular-Aided Inertial Navigation

 

Collaborative Cellular-Aided Inertial Navigation

This video presents the first experimental demonstration of multiple unmanned aerial vehicles (UAVs) aiding their on-board inertial navigation systems (INSs) by sharing mutual pseudorange observables extracted from cellular transmitters and communicating their own inertial measurement unit (IMU) data. While GPS is available, the UAVs use their INSs aided by GPS and cellular signals to navigate while simultaneously mapping the cellular transmitters. When GPS signals become unavailable, the UAVs navigate exclusively with their INSs aided by cellular pseudoranges while simultaneously mapping the cellular transmitters (i.e., performing centralized collaborative radio SLAM). Results demonstrate that the exploitation of free ambient cellular signals of opportunity (SOPs) in the environment significantly reduces INS errors in the absence of GPS.

 
Collaborative Cellular-Aided Inertial Navigation

 

Ground Vehicle Navigation with LTE Signals: SSS vs. CRS

This video presents ground vehicle navigation using two different reference signals in a semi-urban environment in long-term evolution (LTE) systems: the secondary synchronization signal (SSS) and the cell-specific reference signal (CRS). The transmission bandwidth of the SSS is less than 1 MHz, leading to low time-of-arrival (TOA) estimation accuracy in a multipath environment. The CRS is more robust in multipath environments due to its higher transmission bandwidth, which can be as high as 20 MHz. The navigation solutions estimated from the SSS only and from the SSS aided by the CRS are shown. For the SSS-only solution, a computationally-efficient receiver was designed. For the CRS-aided SSS solution, the channel impulse response was estimated using the CRS and used as a feedback into the SSS receiver tracking loops. The results show 5 times improvement in the root mean squared error (RMSE) by using the CRS-aided SSS receiver over the SSS receiver.

 
 


 

Cellular-Aided Inertial Navigation

This video presents the first experimental demonstration of an unmanned aerial vehicle's (UAV's) inertial navigation system (INS) being aided by a cellular signal of opportunity (SOP). While GPS is available, the UAV uses the INS aided by GPS and cellular signals to navigate while simultaneously mapping the cellular SOP. When GPS signals become unavailable, the UAV navigates exclusively with the INS aided by the cellular SOP while simultaneously mapping the cellular SOP (i.e., performing radio SLAM). Results demonstrate that the exploitation of free ambient cellular signals in the environment significantly reduces INS errors in the absence of GPS and bounds the INS drift.

Cellular-Aided Inertial Navigation

 

UAV Navigating with Cellular LTE Signals

This video presents the first experimental demonstration of a UAV navigating exclusively with cellular LTE signals. In this video, a DJI Matrice 600 is equipped with a cellular consumer-grade 800/1900 MHz omnidirectional antenna for receiving LTE signals. The LTE signals were down-mixed and sampled via an Ettus E312 USRP. Then, the signals were processed using the LTE software-defined receiver (SDR) developed by ASPIN Laboratory. The LTE navigation solution is compared to the UAV's true trajectory, which is obtained from the UAV's sensor suite (e.g., GPS, IMU, barometer, etc.).

UAV Navigating with Cellular LTE Signals

 

UAV Navigating with Cellular CDMA Signals

This video presents the first experimental demonstration of a UAV navigating exclusively with cellular CDMA signals. In this video, a DJI Matrice 600 is equipped with a cellular consumer-grade 800/1900 MHz omnidirectional antenna for receiving CDMA signals. The CDMA signals were down-mixed and sampled via an Ettus E312 USRP. Then, the signals were processed using the LabVIEW-based cellular CDMA software-defined receiver (SDR) developed by ASPIN Laboratory. The UAV is receiving information about ambient cellular signals from a reference station deployed in the University of California, Riverside campus. The cellular CDMA navigation solution is compared to the solution obtained from the UAV's on-board navigation system (the A3 flight controller), which consists of a GPS receiver, an IMU, a barometer, and a magnetometer.

  UAV Navigating with Cellular CDMA Signals

 

GPS Vertical Dilution of Precision Reduction using Signals of Opportunity

This video presents simulated and experimental demonstrations of exploiting signals of opportunity (SOPs), e.g., cellular signals, to reduce the relatively large vertical errors that are intrinsic to a GPS-only navigation solution. Since cellular signals are transmitted from towers located in favorable geometric configurations, fusing them with GPS signals significantly improves the accuracy when compared to a GPS-only navigation solution.