The cost of unmanned aerial vehicle (UAV) systems includes more than simply the airframe and payload. During operations in Bosnia and Afghanistan, the Predator UAV required support of 50 to 100 people ranging in skill set from ground pilots, to mechanics, to the guards and cooks who supported the flight operation personnel. The affordability of UAV systems will be reduced if support personnel can be eliminated as a dominant recurring cost factor. Full autonomy through the injection of onboard intelligence is a solution to affordability. For the past decade, teams have been pushing the state of the art in intelligent aerial robotic behavior as part of the International Aerial Robotics Competition.
{"title":"Full autonomy of intelligent flight","authors":"R. Michelson","doi":"10.1109/IDC.2002.995360","DOIUrl":"https://doi.org/10.1109/IDC.2002.995360","url":null,"abstract":"The cost of unmanned aerial vehicle (UAV) systems includes more than simply the airframe and payload. During operations in Bosnia and Afghanistan, the Predator UAV required support of 50 to 100 people ranging in skill set from ground pilots, to mechanics, to the guards and cooks who supported the flight operation personnel. The affordability of UAV systems will be reduced if support personnel can be eliminated as a dominant recurring cost factor. Full autonomy through the injection of onboard intelligence is a solution to affordability. For the past decade, teams have been pushing the state of the art in intelligent aerial robotic behavior as part of the International Aerial Robotics Competition.","PeriodicalId":385351,"journal":{"name":"Final Program and Abstracts on Information, Decision and Control","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114863978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, a new algorithm is presented to adaptively estimate the direction of arrivals (DOAs) of multiple moving targets when linear equispaced sensor array is used for making the measurements. This algorithm is based on an extension of differential MUSIC method. It can also discriminate sources and their multi-paths. The results obtained by this algorithm are then applied as input to a nonlinear state linear measurements unscented Kalman filter. The unscented Kalman filter is also adapted to maneuver the target tracking. This algorithm gives 50 percent reduction in the computation and memory requirements over an unscented filter based tracker.
{"title":"An optimal integrated tracking (ITS) for passive DOA tracking using unscented Kalman filter","authors":"C. Vijay Kumar, R. Rajagopal, R. Kiran","doi":"10.1109/IDC.2002.995407","DOIUrl":"https://doi.org/10.1109/IDC.2002.995407","url":null,"abstract":"In this paper, a new algorithm is presented to adaptively estimate the direction of arrivals (DOAs) of multiple moving targets when linear equispaced sensor array is used for making the measurements. This algorithm is based on an extension of differential MUSIC method. It can also discriminate sources and their multi-paths. The results obtained by this algorithm are then applied as input to a nonlinear state linear measurements unscented Kalman filter. The unscented Kalman filter is also adapted to maneuver the target tracking. This algorithm gives 50 percent reduction in the computation and memory requirements over an unscented filter based tracker.","PeriodicalId":385351,"journal":{"name":"Final Program and Abstracts on Information, Decision and Control","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115825060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A technique for fast target tracking using active sonar has been extended to multiple dimensions. Several issues concerning this implementation of the technique are discussed and examples showing the performance of the technique are presented.
{"title":"Using active sonar to track fast targets via deliberate range ambiguity","authors":"F. Fletcher, D. J. Kershaw","doi":"10.1109/IDC.2002.995425","DOIUrl":"https://doi.org/10.1109/IDC.2002.995425","url":null,"abstract":"A technique for fast target tracking using active sonar has been extended to multiple dimensions. Several issues concerning this implementation of the technique are discussed and examples showing the performance of the technique are presented.","PeriodicalId":385351,"journal":{"name":"Final Program and Abstracts on Information, Decision and Control","volume":"179 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123211798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Presents an algorithm for the stabilization of an uncertain discrete-time linear system via a limited capacity channel. In this control system, the actuator can only receive information from the sensor via a limited capacity channel. The approach taken is a Lyapunov type approach using a polyhedral Lyapunov function of a specific form.
{"title":"State feedback stabilization of uncertain discrete-time linear systems via a limited capacity communication channel","authors":"I. Petersen, A. Savkin","doi":"10.1109/IDC.2002.995399","DOIUrl":"https://doi.org/10.1109/IDC.2002.995399","url":null,"abstract":"Presents an algorithm for the stabilization of an uncertain discrete-time linear system via a limited capacity channel. In this control system, the actuator can only receive information from the sensor via a limited capacity channel. The approach taken is a Lyapunov type approach using a polyhedral Lyapunov function of a specific form.","PeriodicalId":385351,"journal":{"name":"Final Program and Abstracts on Information, Decision and Control","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129813116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We present a framework for controller design for nonlinear sampled-data differential inclusions based on their approximate discrete-time models. The results are presented for the case of fixed sampling periods and the considered stability is with respect to arbitrary (not necessarily compact) sets.
{"title":"Control of nonlinear sampled-data systems with fixed sampling periods via their approximate discrete-time models","authors":"D. Nešić, A. Teel","doi":"10.1109/IDC.2002.995384","DOIUrl":"https://doi.org/10.1109/IDC.2002.995384","url":null,"abstract":"We present a framework for controller design for nonlinear sampled-data differential inclusions based on their approximate discrete-time models. The results are presented for the case of fixed sampling periods and the considered stability is with respect to arbitrary (not necessarily compact) sets.","PeriodicalId":385351,"journal":{"name":"Final Program and Abstracts on Information, Decision and Control","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129415732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We study the computation of the structural invariants of singular linear systems and the transformation of a system pencil to a Kronecker canonical form. A compressed state space system is defined and then transformed into a structural canonical form, in which the structure invariants of the original singular system can be directly identified.
{"title":"Computation of structural invariants of singular linear systems","authors":"Xinmin Liu, B.M. Chen, Zongli Lin","doi":"10.1109/IDC.2002.995362","DOIUrl":"https://doi.org/10.1109/IDC.2002.995362","url":null,"abstract":"We study the computation of the structural invariants of singular linear systems and the transformation of a system pencil to a Kronecker canonical form. A compressed state space system is defined and then transformed into a structural canonical form, in which the structure invariants of the original singular system can be directly identified.","PeriodicalId":385351,"journal":{"name":"Final Program and Abstracts on Information, Decision and Control","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121169691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
/sup O/ver-the-horizon radar (OTHR) provides wide area surveillance coverage beyond the line-of-sight horizon by the propagation of HF signals via the ionosphere. Targets with a radial velocity relative to the radar site are detected by the Doppler component of the received radar signal. A network of OTHRs with overlapping coverage provides for the detection and tracking of targets irrespective of target velocity. When tracks are formed by each radar in the network, multi-radar track fusion is necessary to clarify the surveillance picture. In addition, multipath ionospheric propagation conditions may yield multiple tracks for each target and for each radar. In this paper, a multi-radar multipath track fusion algorithm (MRMPTF) is outlined, extending the single radar multipath track fusion (MPTF) algorithm previously developed. The impact of OTHR track registration errors is discussed, and the equivalence of alternative OTHR track fusion architectures is shown.
{"title":"Fusion of multipath tracks for a network of over-the-horizon radars","authors":"M. Rutten, D. J. Percival","doi":"10.1109/IDC.2002.995395","DOIUrl":"https://doi.org/10.1109/IDC.2002.995395","url":null,"abstract":"/sup O/ver-the-horizon radar (OTHR) provides wide area surveillance coverage beyond the line-of-sight horizon by the propagation of HF signals via the ionosphere. Targets with a radial velocity relative to the radar site are detected by the Doppler component of the received radar signal. A network of OTHRs with overlapping coverage provides for the detection and tracking of targets irrespective of target velocity. When tracks are formed by each radar in the network, multi-radar track fusion is necessary to clarify the surveillance picture. In addition, multipath ionospheric propagation conditions may yield multiple tracks for each target and for each radar. In this paper, a multi-radar multipath track fusion algorithm (MRMPTF) is outlined, extending the single radar multipath track fusion (MPTF) algorithm previously developed. The impact of OTHR track registration errors is discussed, and the equivalence of alternative OTHR track fusion architectures is shown.","PeriodicalId":385351,"journal":{"name":"Final Program and Abstracts on Information, Decision and Control","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131782751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Tsimbinos, W. Marwood, A. Beaumont-Smith, C. Lim
Error table compensation is one technique that can be used to improve the spurious free dynamic range of high speed A/D converters. This paper gives details of an error table compensator system that uses a VLSI chip incorporating a transversal filter programmed as a wideband differentiator, some additional on chip circuits, and a lookup table that is stored in external memory. The 10 GOPS transversal filter differentiator chip was designed and fabricated in a 0.35 /spl mu/m CMOS process, has programmable tap weights, and can operate at a maximum clock rate of 200 MHz. The results of this paper show that this error table compensation system is capable of providing up to 13 dB improvement in the dynamic range of typical high speed A/D converters. This may result in more reliable detection of weak signals of interest.
{"title":"Results of A/D converter compensation with a VLSI chip","authors":"J. Tsimbinos, W. Marwood, A. Beaumont-Smith, C. Lim","doi":"10.1109/IDC.2002.995413","DOIUrl":"https://doi.org/10.1109/IDC.2002.995413","url":null,"abstract":"Error table compensation is one technique that can be used to improve the spurious free dynamic range of high speed A/D converters. This paper gives details of an error table compensator system that uses a VLSI chip incorporating a transversal filter programmed as a wideband differentiator, some additional on chip circuits, and a lookup table that is stored in external memory. The 10 GOPS transversal filter differentiator chip was designed and fabricated in a 0.35 /spl mu/m CMOS process, has programmable tap weights, and can operate at a maximum clock rate of 200 MHz. The results of this paper show that this error table compensation system is capable of providing up to 13 dB improvement in the dynamic range of typical high speed A/D converters. This may result in more reliable detection of weak signals of interest.","PeriodicalId":385351,"journal":{"name":"Final Program and Abstracts on Information, Decision and Control","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122341232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Several sensor fusion algorithms for estimating the flight parameters of an unmanned air vehicle are presented. These include the classic linear Kalman filter and unscented Kalman filter. Two methods for improving the ability of the linear Kalman filter in estimating a nonlinear plant are proposed. The advantages and disadvantages of each algorithm are illustrated through simulation using a nonlinear six-degree-of-freedom model of the aircraft and simple sensor models.
{"title":"Sensor fusion algorithms for unmanned air vehicles","authors":"M. Niculescu","doi":"10.1109/IDC.2002.995367","DOIUrl":"https://doi.org/10.1109/IDC.2002.995367","url":null,"abstract":"Several sensor fusion algorithms for estimating the flight parameters of an unmanned air vehicle are presented. These include the classic linear Kalman filter and unscented Kalman filter. Two methods for improving the ability of the linear Kalman filter in estimating a nonlinear plant are proposed. The advantages and disadvantages of each algorithm are illustrated through simulation using a nonlinear six-degree-of-freedom model of the aircraft and simple sensor models.","PeriodicalId":385351,"journal":{"name":"Final Program and Abstracts on Information, Decision and Control","volume":"292 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121263417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this article we consider a dynamic M-ary detection problem when Markov chains are observed through a doubly stochastic Poisson process. These systems are fully specified by a candidate set of parameters, whose elements are, a rate matrix for the Markov chain and a vector of Poisson intensities for the observation model. Further, we suppose these parameter sets can switch according to the state of an unobserved Markov chain and thereby produce an observation process generated by time varying (jump stochastic) parameter sets. Given such an observation process and an assumed collection of models, we compute a filter whose solution is the estimated probabilities of each model parameter set explaining the observation. By defining a new augmented state process, then applying the method of reference probability, we compute matrix-valued dynamics whose solutions estimate joint probabilities for all combinations of candidate model parameter sets, and values taken by the indirectly observed state process. These matrix-valued dynamics satisfy a stochastic integral equation with a Lebesgue-Stieltjes integrator. Using the gauge transformation techniques, we compute robust matrix-valued dynamics for the joint probabilities on the augmented state space. In these new dynamics the observed Poisson process appears as a parameter in the fundamental matrix of a linear ordinary differential equation, rather than an integrator in a stochastic integral equation.
{"title":"Robust detection filters for jump Markov systems with doubly stochastic Poisson process models","authors":"W. P. Malcolm, R. Elliott","doi":"10.1109/IDC.2002.995386","DOIUrl":"https://doi.org/10.1109/IDC.2002.995386","url":null,"abstract":"In this article we consider a dynamic M-ary detection problem when Markov chains are observed through a doubly stochastic Poisson process. These systems are fully specified by a candidate set of parameters, whose elements are, a rate matrix for the Markov chain and a vector of Poisson intensities for the observation model. Further, we suppose these parameter sets can switch according to the state of an unobserved Markov chain and thereby produce an observation process generated by time varying (jump stochastic) parameter sets. Given such an observation process and an assumed collection of models, we compute a filter whose solution is the estimated probabilities of each model parameter set explaining the observation. By defining a new augmented state process, then applying the method of reference probability, we compute matrix-valued dynamics whose solutions estimate joint probabilities for all combinations of candidate model parameter sets, and values taken by the indirectly observed state process. These matrix-valued dynamics satisfy a stochastic integral equation with a Lebesgue-Stieltjes integrator. Using the gauge transformation techniques, we compute robust matrix-valued dynamics for the joint probabilities on the augmented state space. In these new dynamics the observed Poisson process appears as a parameter in the fundamental matrix of a linear ordinary differential equation, rather than an integrator in a stochastic integral equation.","PeriodicalId":385351,"journal":{"name":"Final Program and Abstracts on Information, Decision and Control","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117261785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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