Applied Millimeter Wave Radar Vibrometry

In this dissertation, novel uses of millimeter-wave (mmW) radars are developed and analyzed. While automotive mmW radars have been ubiquitous in advanced driver assistance systems (ADAS), their ability to sense motions at sub-millimeter scale allows them to also find application in systems that require accurate measurements of surface vibrations. While laser Doppler vibrometers (LDVs) are routinely used to measure such vibrations, the lower size, weight, power, and cost (SWAPc) of mmW radars make vibrometry viable for a variety of new applications. In this work, we consider two such applications: everything-to-vehicle (X2V) wireless communications and non-acoustic human speech analysis.

Within this dissertation, a wireless communication system that uses the radar as a vibrometer is introduced. This system, termed vibrational radar backscatter communications (VRBC), receives messages by observing phase modulations on the radar signal that are caused by vibrations on the surface of a transponder over time. It is shown that this form of wireless communication provides the ability to simultaneously detect, isolate, and decode messages from multiple sources thanks to the spatial resolution of the radar. Additionally, VRBC requires no RF emission on the end of the transponder. Since automotive radars and the conventional X2V solutions are often at odds for spectrum allocations, this characteristic of VRBC is incredibly valuable.

Using an off-the-shelf, resonant transponder, a real VRBC data collection is presented and used to demonstrate the signal processing techniques necessary to decode a VRBC message. This real data collection proves to achieve a data rate just under 100 bps at approximately 5 meters distance. Rates of this scale can provide warning messages or concise situational awareness information in applications such as X2V, but naturally higher rates are desirable. For that reason, this dissertation includes discussion on how to design a more optimal VRBC system via transponder design, messaging scheme choice, and using any afforded flexibility in radar parameter choice.

Through the use of an analytical upper bound on VRBC rate and simulation results, we see that rates closer to 1 kbps should be achievable for a transponder approximately the size of a license plate at ranges under 200 meters. The added benefits of requiring no RF spectrum or network scheduling protocols uniquely positions VRBC as a desirable solution in spaces like X2V over commonly considered, higher rate solutions such as direct short range communications (DSRC).

Upon implementing a VRBC system, a handful of complications were encountered. This document designates a full chapter to solving these cases. This includes properly modeling intersymbol interference caused by resonant surfaces and utilizing sequence detection methods rather than single symbol maximum likelihood methods to improve detection in these cases. Additionally, an analysis on what an ideal clutter filter should look like and how it can begin to be achieved is presented. Lastly, a method for mitigating platform vibrational noise at both the radar and the transponder are presented. Using these methods, message detection errors are better avoided, though more optimal system design fundamentally proves to limit what rates are achievable.

Towards non-acoustic human speech analysis, it is shown in this dissertation that the vibrations of a person's throat during speech generation can be accurately captured using a mmW radar. These measurements prove to be similar to those achieved by the more expensive vibrometry alternative of an LDV with less than 10 dB of SNR depreciation at the first two speech harmonics in the signal's spectrogram. Furthermore, we find that mmW radar vibrometry data resembles a low-pass filtered version of its corresponding acoustic data. We show that this type of data achieves 53% performance in a speaker identification system as opposed to 11\% in a speech recognition system. This performance suggests potential for a mmW radar vibrometry in context-blind speaker identification systems if the performance of the speaker identification system can be further improved without causing the context of the speech more recognizable.

In this dissertation, mmW radar vibrational returns are modelled and signal processing chains are provided to allow for these vibrations to be estimated and used in application. In many cases, the work outlined could be used in other areas of mmW radar vibrometry even though it was originally motivated by potentially unrelated applications. It is the hope of this dissertation that the provided models, signal processing methods, visualizations, analytical bound, and results not only justify mmW radar in human speech analysis and backscatter communications, but that they also contribute to the community's understanding of how certain vibrational movements can be best observed, processed, and made useful more broadly.