In this thesis, the synergy between millimeter-wave (mmWave) imaging and wireless communications is used to achieve high accuracy user localization and mapping (SLAM) mobile users in an uncharted environment. Such capability is enabled by taking advantage of the high-resolution image of both line-of-sight (LoS) and non-line-of-sight (NLoS) objects that mmWave imaging provides, and by utilizing angle of arrival (AoA) and time of arrival (ToA) estimators from communications. The motivations of this work are as follows: first, enable accurate SLAM from a single viewpoint i.e., using only one antenna array at the base station without any prior knowledge of the environment. The second motivation is the ability to localize in NLoS-only scenarios where the user signal may experience more than one reflection until it reaches the base station. As such, this proposed work will not make any assumptions on what region the user is and will use mmWave imaging techniques that will work for both near and far field region of the base station and account for the scattering properties of mmWave. Similarly, a near field signal model is developed to correctly estimate the AoA regardless of the user location.

This SLAM approach is enabled by reconstructing the mmWave image of the environment as seen by the base station. Then, an uplink pilot signal from the user is used to estimate both AoA and ToA of the dominant channel paths. Finally, AoA/ToA information is projected into the mmWave image to fully localize the user. Simulations using full-wave electromagnetic solvers are carried out to emulate an environment both in the near and far field. Then, to validate, an experiment carried in laboratory by creating a simple two-dimensional scenario in the 220-300 GHz range using a synthesized 13-cm linear antenna array formed by using vector network analyzer extenders and a one-dimensional linear motorized stage that replicates the base station. After taking measurements, this method successfully reconstructs the image of the environment and localize the user position with centimeter accuracy.

In the past half century, low-power wireless signals from portable radar sensors, initially continuous-wave (CW) radars and more recently ultra-wideband (UWB) radar systems, have been successfully used to detect physiological movements of stationary human beings.

The thesis starts with a careful review of existing signal processing techniques and state of the art methods possible for vital signs monitoring using UWB impulse systems. Then an in-depth analysis of various approaches is presented.

Robust heart-rate monitoring methods are proposed based on a novel result: spectrally the fundamental heartbeat frequency is respiration-interference-limited while its higher-order harmonics are noise-limited. The higher-order statistics related to heartbeat can be a robust indication when the fundamental heartbeat is masked by the strong lower-order harmonics of respiration or when phase calibration is not accurate if phase-based method is used. Analytical spectral analysis is performed to validate that the higher-order harmonics of heartbeat is almost respiration-interference free. Extensive experiments have been conducted to justify an adaptive heart-rate monitoring algorithm. The scenarios of interest are, 1) single subject, 2) multiple subjects at different ranges, 3) multiple subjects at same range, and 4) through wall monitoring.

A remote sensing radar system implemented using the proposed adaptive heart-rate estimation algorithm is compared to the competing remote sensing technology, a remote imaging photoplethysmography system, showing promising results.

State of the art methods for vital signs monitoring are fundamentally related to process the phase variation due to vital signs motions. Their performance are determined by a phase calibration procedure. Existing methods fail to consider the time-varying nature of phase noise. There is no prior knowledge about which of the corrupted complex signals, in-phase component (I) and quadrature component (Q), need to be corrected. A precise phase calibration routine is proposed based on the respiration pattern. The I/Q samples from every breath are more likely to experience similar motion noise and therefore they should be corrected independently. High slow-time sampling rate is used to ensure phase calibration accuracy. Occasionally, a 180-degree phase shift error occurs after the initial calibration step and should be corrected as well. All phase trajectories in the I/Q plot are only allowed in certain angular spaces. This precise phase calibration routine is validated through computer simulations incorporating a time-varying phase noise model, controlled mechanic system, and human subject experiment.