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The incorporation of digital modulation into radar systems poses various challenges in the field of radar design, but it also offers a potential solution to the shrinking availability of low-noise operating environments as the number of radar applications increases. Additionally, digital systems have reached a point where available components and technology can support higher speeds than ever before. These advancements present new avenues for radar design, in which digitally controlled phase-modulated continuous wave (PMCW) radar systems can look to support multiple collocated radar systems with low radar-radar interference. This paper proposes a reconfigurable PMCW radar for use in vital sign detection and gesture recognition while utilizing digital carrier modulation and compares the radar responses of various modulation schemes. Binary sequences are used to introduce phase modulation to the carrier wave by use of a field programable gate array (FPGA), allowing for flexibility in the modulation speed and binary sequence. Experimental results from the radar demonstrate the differences between CW and PMCW modes when measuring the respiration rate of a human subject and in gesture detection. 

Indoor passive radar has gained traction as a method for measuring small-amplitude motions without requiring a cooperative signal to be transmitted by the sensor. Ubiquitous signals such as Wi-Fi and Bluetooth may be used as illuminators of opportunity in order to measure the motion of various targets. Both the direct, unmodulated signal as well as the Doppler-shifted signal are received at the radar and are used for down-conversion to baseband. Since there is no cooperative local oscillator used in passive radar, it is not currently possible to effectively extract both the I and Q channel data making null-point detection a returning problem. In this work, the null-point detection problem is analyzed theoretically to develop a simulation model for passive radar sensing. Using this model, an in-depth analysis is undertaken in order to determine the effectiveness of methods such as channel selection, frequency tuning, or multi-band/multi-static sensing in removing or mitigating the null-point detection problem. The results demonstrate that despite the presence of the null-point issue, it is possible to reduce its impact on motion detection and optimize the detection sensitivity.