Monopulse processing and tracking of maneuvering targets

Glass, John David

Title:

Monopulse processing and tracking of maneuvering targets

dc.contributor.advisor	Lanterman, Aaron D.
dc.contributor.author	Glass, John David
dc.contributor.committeeMember	Blair, William
dc.contributor.committeeMember	Williams, Doug
dc.contributor.committeeMember	Dieci, Luca
dc.contributor.committeeMember	McClellan, James H.
dc.contributor.department	Electrical and Computer Engineering
dc.date.accessioned	2015-06-08T18:35:11Z
dc.date.available	2015-06-08T18:35:11Z
dc.date.created	2015-05
dc.date.issued	2015-04-06
dc.date.submitted	May 2015
dc.date.updated	2015-06-08T18:35:11Z
dc.description.abstract	As part of the processing of tracking targets, surveillance radars detect the presence of targets and estimate their locations. This dissertation re-examines some of the often ignored practical considerations of radar tracking. With the advent of digital computers, modern radars now use sampled versions of received signals for processing. Sampling rates used in practice result in the bin-straddling phenomenon, which is often treated as an undesired loss in signal power. Here, a signal model that explicitly models the sampling process is used in the derivation of the average loglikelihood ratio test (ALLRT), and its detection performance is shown to defeat the bin-straddling losses seen in traditional radar detectors. In monopulse systems, data samples are taken from the sum and difference channels, by which a target direction-of-arrival (DOA) estimate can be formed. Using the same signal model, we derive new estimators for target range, strength, and DOA and show performance benefits over traditional monopulse techniques that are predominant in practice. Since tracking algorithms require an error variance report on target parameter estimates, we propose using the generalized Cramer-Rao lower bound (GCRLB), which is the CRLB evaluated at estimates rather than true values, as an error variance report. We demonstrate the statistical efficiency and variance consistency of the new estimators. With several parameter estimates collected over time, tracking algorithms are used to compute track state estimates and predict future locations. Using agile- beam surveillance radars with programmable energy waveforms, optimal scheduling of radar resources is a topic of interest. In this dissertation, we focus on the energy management considerations of tracking highly maneuverable aircraft. A comparison between two competing interacting multiple model (IMM) filter configurations is made, and a recently proposed unbiased mixing procedure is extended to the case of three modes. Finally, we introduce the radar management operating curve (RMOC), which shows the fundamental tradeoff in radar time and energy, to aid radar designers in the selection of an overall operating signal-to-noise level.
dc.description.degree	Ph.D.
dc.format.mimetype	application/pdf
dc.identifier.uri	http://hdl.handle.net/1853/53556
dc.language.iso	en_US
dc.publisher	Georgia Institute of Technology
dc.subject	Monopulse radar
dc.subject	Radar detection
dc.subject	Monopulse processing
dc.subject	Interacting multiple model filter
dc.subject	Radar resource management
dc.title	Monopulse processing and tracking of maneuvering targets
dc.type	Text
dc.type.genre	Dissertation
dspace.entity.type	Publication
local.contributor.advisor	Lanterman, Aaron D.
local.contributor.corporatename	School of Electrical and Computer Engineering
local.contributor.corporatename	College of Engineering
relation.isAdvisorOfPublication	8a33b73f-88b1-4907-b2f6-307f5ad37738
relation.isOrgUnitOfPublication	5b7adef2-447c-4270-b9fc-846bd76f80f2
relation.isOrgUnitOfPublication	7c022d60-21d5-497c-b552-95e489a06569
thesis.degree.level	Doctoral