Phenomenological Study of Radar Scattering at High Millimeter-Wave Frequencies in Support of Autonomous Vehicles

There has been significant investment in realizing autonomous vehicles technology. Despite tremendous efforts and investments, the initial optimism in achieving total autonomy has not yet been materialized. This is not totally surprising as the required false alarm rate and probability of detection are very stringiest for a complex navigation problem which includes fast-changing scenarios of many dynamic obstacles of different kinds. This situation is often exacerbated by inclement weather and road conditions. In an effort to improve sensors’ capabilities, this thesis focuses on examining the applications and advantages of polarimetric J-band (220 – 325 GHz) radars for driverless cars. Automotive radars operating at lower J-band frequencies are envisioned to replace the current 77-GHz systems in vehicles for their superior resolution, compact size, and wider bandwidth. This dissertation aims at studying the polarimetric radar response of typical traffic scenes at this frequency. For highly automated vehicles, identifying each target on the road and its vicinity is crucial in planning the navigation and ensuring safety for all. Characterization of the radar backscatter from various objects enables their identification in traffic scenes and is necessary for optimizing the design of automotive sensors. The polarization signature of different targets can help with semantic mapping of targets on the road, especially for those targets that may be in the same range and Doppler bin. Considering vehicles as the most critical objects for automotive radars to detect and locate, a thorough study is conducted to investigate the response of vehicles from different aspects. This experimental study aims to identify the scattering phase centers on different vehicle bodies and determine the statistics of the radar return. A vehicle’s orientation and movement can be predicted from these features. In addition, the statistical parameters of the response are very distinct, and hence accurate determination can be made. Another study focuses on investigating and characterizing the response from various road surfaces. The knowledge of the expected radar signal from these surfaces is not only helpful in developing detection algorithms for other objects in the presence of this background but also for assessing the road conditions, such as detecting the presence of water, ice, snow, or harmful objects and debris on the road. Radar backscatter models are developed for various surfaces and conditions that actual measurements can be classified based on their correlation to these models. One of the most vulnerable road users is pedestrians. The radar backscatter cross-section of the human body (~ -17 dBsm) is significantly less than that of a typical vehicle (~ 0 dBsm). The identification of pedestrians also should be performed at a further distance to allow a vehicle to react appropriately in a timely manner. As a result, backscattering from human subjects should be thoroughly examined to determine the radar return level and offer the most effective detection and identification techniques. Extensive experimental research that resulted in characterizing the polarimetric radar response and the micro-Doppler spectrum from human subjects is carried out as part of this thesis.PHDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/174574/1/alaqeel_1.pd