Joint IEEE 802.11 Communications and Radar for Vehicular Forward Collision Detection
Recent mandates for automation in vehicular transportation safety have increased demand for radar applications such as forward collision detection and avoidance. The majority of current implementations of vehicular radar are mmWave radars, which are expensive and exhibit multiple security vulnerabilities. We have demonstrated the feasibility of a secure and cost-efficient IEEE 802.11-based system with radar capabilities via implementation and testing. Measurements demonstrate that our solution delivers meter level accuracy for single-target detection with just 20 MHz of spectrum provided by IEEE 802.11, supporting significant potential cost reduction of future releases of vehicular radar.
Our system assumes that the IEEE 802.11 channel model adheres to the two-path complex baseband link model, such that there is a dominant direct path and weaker reflected path. By supposing that the mean-normalized channel energy can be modeled as a sinusoid, we perform a brute-force minimization algorithm that determines the best-fit sinusoid corresponding to a specific range with respect to the received channel estimates. The subsequent range is returned as the detected range of the closest target to the device.
This prototype was built using hardware from National Instruments and coded fully in LabVIEW. The system consists of a NI-USRP RIO connected to a desktop machine equipped with LabVIEW FPGA and two 23 dBi broadband patch antennas. The desktop extracts channel estimates via direct memory access and is responsible for algorithm processing. Overall, the system operates at 4.89 GHz with 20 MHz of bandwidth with a 10 dBm transmit power gain.
We have demonstrated meter-level accuracy for single-target detection with only 20 MHz of bandwidth up to 30m. Theoretically, the system has a maximum range of up to 120m. Compared to current implementations of vehicular radar, IEEE 802.11-based radar more cost-effective and secure. In addition, it is directly integrable into the DSRC protocol (IEEE 802.11p) and can be implemented on vehicles with no previous Wi-Fi or radar capabilities. Currently, we are focused on extending these results by implementing forward lane isolation, multiple target detection, and a joint IEEE 802.11 radar and DSRC advanced localization system.
 E. Yeh, R. Daniels, and R. Heath, Jr., “Forward collision vehicular RADAR with IEEE 802.11: feasibility demonstration through measurements,” The University of Texas at Austin, 2015.
This research is partially supported by the U.S. Department of Transportation through the Data-Supported Transportation Operations and Planning (D-STOP) Tier 1 University Transportation Center and by the Texas Department of Transportation under Project 0-6877 entitled Communications and Radar-Supported Transportation Operations and Planning (CAR-STOP).