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Fully adaptive radar for detection and tracking

Christiansen, Jonas Myhre
http://orcid.org/0000-0003-2270-8459
http://rave.ohiolink.edu/etdc/view?acc_num=osu1587093543249087

Abstract Details

2020, Doctor of Philosophy, Ohio State University, Electrical and Computer Engineering.
This thesis will shown the development of an experimental radar testbed to test cognitive radar applications. The testbed is built upon the Universal Software Radio Peripheral (USRP) X-310, which is a member of a line of software de_ned radio (SDR)s available from Ettus. The testbed can, therefore, be kept at low cost and hence affordable to academia and smaller research projects. Experimental activities presented the system's detection range for a large airliner as approximately 5.5km, for a small aircraft as approximately 2.8km, and a detection range of a small unmanned aerial vehicle (UAV) as more than 350m. An experiment was conducted tracking a small UAV, illustrating that the system is capable of tracking a small target. A method for absolute radar cross section (RCS) calibration and channel characterization is shown. The thesis has also shown the development of a novel cost function for track update interval control using a fully adaptive radar (FAR) framework. An algorithm has been developed for a tracking system with track update interval control using the cost function developed. A simulator written in Matlab tested the algorithm in a set of scenarios. The cognitive radar (CR) experimental testbed was used as a radar system with the adaptive track update interval algorithm implemented. The algorithm was tested through a simple scenario of a UAV ying between two waypoints, and the waypoints were radially to the radar system. Finally, the thesis shows an adaptive beam scheduling method for radar surveillance, where a target present/absent function is used in a FAR framework to increase the cumulative detection performance. Simulation results for multiple maneuvering targets are shown, where the cumulative detection performance for both targets is close to a 100% over the raster beam scheduling method. A many target scenario is shown as well, where the cumulative detection performance is lower than for one or two targets; however, the performance is still close to a 100% improvement. The method uses no other prior information than the signal to noise ratio (SNR) values for each range-angle cell; hence it is not dependent on any heuristics.
Graeme Smith (Advisor)
Joel Johnson (Advisor)
Robert Burkholder (Committee Member)
Emre Ertin (Committee Member)
Daniel Wozniak (Committee Member)
181 p.
Electrical Engineering
Radar; fully adaptive radar; cognitive radar; software defined radio; signal processing

Recommended Citations

Citations

  • Christiansen, J. M. (2020). Fully adaptive radar for detection and tracking [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1587093543249087

    APA Style (7th edition)

  • Christiansen, Jonas. Fully adaptive radar for detection and tracking. 2020. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1587093543249087.

    MLA Style (8th edition)

  • Christiansen, Jonas. "Fully adaptive radar for detection and tracking." Doctoral dissertation, Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1587093543249087

    Chicago Manual of Style (17th edition)

osu1587093543249087
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This open access ETD is published by The Ohio State University and OhioLINK.