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Multiplicative processing of stepped frequency measurements for super-resolution range profile estimation: a thesis in Electrical Engineering
Thesis   Open access

Multiplicative processing of stepped frequency measurements for super-resolution range profile estimation: a thesis in Electrical Engineering

Matthew J. Curtis
Master of Science (MS), University of Massachusetts Dartmouth
2018
DOI:
https://doi.org/10.62791/19982

Abstract

Radio -- Monitoring receivers. Radio -- Monitoring receivers
Fine range resolution capability plays a significant role in precision estimation of the distance between a target of interest and a radiating source using radio frequency (RF) sensors. The extraction of this information impacts existing and emerging ranging applications such as remote monitoring of GPS navigation, radio imaging, collision avoidance automation, cardiorespiratory systems, and position location technologies. When a scattered signal is detected by a RF system, the relative phase difference between the transmitted and received signal is analyzed to determine a timing delay, consequently, the range between the radio and the target of interest. Range resolution is a performance metric that defines a waveform’s ability to distinguish between multiple targets while also increasing the accuracy of the range estimate. This metric is inversely proportional to the operating bandwidth of the transmitted signal. Pulse compression waveforms and stepped frequency waveforms have been developed over the years to achieve fine resolution measurements when generating range profiles of targets. A super-resolution technique known as time-delay product processing (TDPP), which utilizes multiplicative processing of stepped frequency measurements to generate range-profiling, is introduced in this thesis to achieve range resolution which is significantly better than that which is commensurate with the actual bandwidth. Simulations are used to study the accuracy and limitations of this technique due to noise and interference. Simulations show that in high signal-to-noise ratio (SNR) environments, the TDPP method using small bandwidths is able to achieve range resolution which is commensurate with those from linear processing of very large bandwidth waveforms. In low SNR scenarios, the TDPP method does not perform as well because its time-bandwidth product is significantly lower. Simulations are complemented by the use of S-band radio measurements from the universal software radio peripheral (USRP™) system. USRP™ is a software defined radio (SDR) that allows for the flexible emulation of a radio system, permitting the user to manipulate tunable RF hardware through the use of software, eliminating time constraints required in the design and testing of a RF system. Processing indoor measurements from the USRP™ system using the TDPP technique further validated the accuracy of the proposed method.
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Curtis M. J. COE MS Thesis 20186.69 MBDownloadView
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