{"title":"Compressive sampling based MVDR spectrum sensing","authors":"Y. Wang, A. Pandharipande, G. Leus","doi":"10.1109/CIP.2010.5604239","DOIUrl":"https://doi.org/10.1109/CIP.2010.5604239","url":null,"abstract":"We propose a compressive sampling (CS) based MVDR spectrum estimator, which estimates the wideband spectrum from the compressed signals with sub-Nyquist-rate sampling. To analyze detection performance, we derive the statistics of the estimated CS MVDR spectrum considering finite samples. We also show that different compression matrices produce different levels of signal leakage and influence the computation of detection thresholds.","PeriodicalId":171474,"journal":{"name":"2010 2nd International Workshop on Cognitive Information Processing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122894290","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}
{"title":"Stable matching for channel access control in cognitive radio systems","authors":"Y. Yaffe, Amir Leshem, E. Zehavi","doi":"10.1109/CIP.2010.5604115","DOIUrl":"https://doi.org/10.1109/CIP.2010.5604115","url":null,"abstract":"In this paper we propose a game theoretic approach to the allocation of channels to multiple cognitive users who share a set of frequencies. The famous Gale-Shapley stable matching algorithm is utilized to compute the channel allocations. We analyze the stable matching performance for the case of cognitive resource allocation and prove that in contrast to the general case, in the cognitive resource allocation problem there is a unique stable matching. We then show that the stable matching has performance very close to the optimal centralized allocation. It always achieves at least half of the total rate of the centralized allocation and under Rayleigh fading it achieves about 96% of the total centralized rate. Comparisons to random channel allocations are also discussed.","PeriodicalId":171474,"journal":{"name":"2010 2nd International Workshop on Cognitive Information Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129785396","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}
{"title":"Adapting a MIMO/phased-array radar transmit beampattern to target location","authors":"D. Fuhrmann, J. P. Browning, M. Rangaswamy","doi":"10.1109/CIP.2010.5604212","DOIUrl":"https://doi.org/10.1109/CIP.2010.5604212","url":null,"abstract":"Proposed MIMO and hybrid MIMO/phased array (HMPAR) radar systems have the potential for tremendous flexibility in the choice of the transmit beampattern, through the selection of multiple transmitted signals. This paper considers how one might exploit that flexibility in light of prior information or uncertainty in target spatial location, for parameter estimation or tracking applications. We first consider an idealized problem of distributing energy across multiple target sites given a prior probability distribution on those sites. It shown that the optimal allocation of energy would be proportional to the square root of the prior probability. Second, we propose a method to approximate this optimal distribution of energy using a MIMO radar or HMPAR radar system. The method chooses signals that realize an intrapulse beamscan over the region of interest, with a nonuniform distribution of scan points matched to the desired distribution of energy.","PeriodicalId":171474,"journal":{"name":"2010 2nd International Workshop on Cognitive Information Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129226097","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}
{"title":"Rapid waveform adaptation for nearly optimal detection in colored interference","authors":"C. W. Rossler, L. Patton","doi":"10.1109/CIP.2010.5604106","DOIUrl":"https://doi.org/10.1109/CIP.2010.5604106","url":null,"abstract":"A cognitive radar can dynamically design its transmit waveform in response to changing environmental knowledge, which may be obtained a priori, estimated online, or both. We consider the detection of targets in wide-sense stationary additive colored Gaussian noise. Cognitive radar has been shown to provide potentially significant improvements for this problem. However, existing algorithms may be too computationally demanding for some scenarios. We present an approach that can be implemented in the most demanding scenarios. This approach trades optimality for reduced computational complexity by computing a large library of nearly optimal waveforms before operation, and retrieving them rapidly at runtime.","PeriodicalId":171474,"journal":{"name":"2010 2nd International Workshop on Cognitive Information Processing","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129522771","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. Balleri, H. Griffiths, K. Woodbridge, C. Baker, M. Holderied
{"title":"Impact of flight trajectory on the detection and selection of flowers by nectar-feeding bats","authors":"A. Balleri, H. Griffiths, K. Woodbridge, C. Baker, M. Holderied","doi":"10.1109/CIP.2010.5604124","DOIUrl":"https://doi.org/10.1109/CIP.2010.5604124","url":null,"abstract":"Echolocating mammals, such as bats, have evolved an excellent ability to detect, select and identify the targets they depend on for their survival by echolocation even in the most challenging environments. They simultaneously adapt their trajectory and diversify transmission parameters such as waveform, bandwidth and time duration, to obtain high level detection and classification performance that is far better than that obtained by modern radar and sonar systems. This paper exploits the information available to the bat along its in-flight trajectory aiming at assessing the impact of choosing the right trajectory on detection and classification performance. A set of experimental data consisting of HRRPs of one inflorescence of Rhytidophyllum auriculatum is analysed and results are discussed and related to the case of radar and sonar systems.","PeriodicalId":171474,"journal":{"name":"2010 2nd International Workshop on Cognitive Information Processing","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128279555","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}
{"title":"Radar waveform design for detection of weapons","authors":"F. Ahmad, M. Amin","doi":"10.1109/CIP.2010.5604230","DOIUrl":"https://doi.org/10.1109/CIP.2010.5604230","url":null,"abstract":"We present waveform design based on signature exploitation techniques for improved detection of weapons in urban sensing applications. We consider a single-antenna monostatic radar system. Under the assumption of exact knowledge of the target orientation and, hence, known impulse response, matched illumination approach is used for optimal target detection. For the case of unknown target orientation, we propose waveform design based on subspace decomposition of the target impulse response matrix corresponding to the various aspect angles. Numerical electromagnetic modeling is used to provide the impulse responses of an AK-47 assault rifle for various target aspect angles relative to the radar. Simulation results depict an improvement in the signal-to-noise-ratio (SNR) at the output of the matched filter receiver for both matched illumination and subspace waveforms as compared to a chirp waveform of the same duration and energy.","PeriodicalId":171474,"journal":{"name":"2010 2nd International Workshop on Cognitive Information Processing","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122382678","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. Candy, D. Chambers, E. Breitfeller, B. Guidry, J. Verbeke, M. Axelrod, K. Sale, A. Meyer
{"title":"Radioactive threat detection with scattering physics: A model-based application","authors":"J. Candy, D. Chambers, E. Breitfeller, B. Guidry, J. Verbeke, M. Axelrod, K. Sale, A. Meyer","doi":"10.1109/CIP.2010.5604145","DOIUrl":"https://doi.org/10.1109/CIP.2010.5604145","url":null,"abstract":"The detection of radioactive contraband is a critical problem in maintaining national security for any country. Emissions from threat materials challenge both detection and measurement technologies especially when concealed by various types of shielding complicating the transport physics significantly. The development of a model-based sequential Bayesian processor that captures both the underlying transport physics including scattering offers a physics-based approach to attack this challenging problem. It is shown that this processor can be used to develop an effective detection technique.","PeriodicalId":171474,"journal":{"name":"2010 2nd International Workshop on Cognitive Information Processing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131198325","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}
{"title":"Utilizing Q-Learning to allow a radar to choose its transmit frequency, adapting to its environment","authors":"L. Wabeke, W. Nel","doi":"10.1109/CIP.2010.5604208","DOIUrl":"https://doi.org/10.1109/CIP.2010.5604208","url":null,"abstract":"Recent research show that utilization of knowledge of the environment can allow a radar system to adapt its processing to improve its performance. Furthermore, a radar system that utilize both a-priori and measured knowledge in an adaptive close loop manner could seem to be cognitive of its environment, able to adapt to changes to optimize performance. Reinforced learning could play a vital role as part of such a closed-loop cognitive radar system. The Q-Learning algorithm is hypothesized to be useful for this cognitive radar domain. This paper investigates the problem of adaptively choosing the radar transmit frequency through application of Q-Learning on measured radar data. A comparison is made against other frequency selection algorithms and its shown that Q-Learning manages to learn a good strategy to adaptively select radar transmit frequency, mostly outperforming the other methods tested in the scenario investigated here.","PeriodicalId":171474,"journal":{"name":"2010 2nd International Workshop on Cognitive Information Processing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132478878","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}
{"title":"On multi-step sensor scheduling via convex optimization","authors":"Marco F. Huber","doi":"10.1109/CIP.2010.5604100","DOIUrl":"https://doi.org/10.1109/CIP.2010.5604100","url":null,"abstract":"Effective sensor scheduling requires the consideration of long-term effects and thus optimization over long time horizons. Determining the optimal sensor schedule, however, is equivalent to solving a binary integer program, which is computationally demanding for long time horizons and many sensors. For linear Gaussian systems, two efficient multi-step sensor scheduling approaches are proposed in this paper. The first approach determines approximate but close to optimal sensor schedules via convex optimization. The second approach combines convex optimization with a branch-and-bound search for efficiently determining the optimal sensor schedule.","PeriodicalId":171474,"journal":{"name":"2010 2nd International Workshop on Cognitive Information Processing","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128438669","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}
{"title":"Foraging behavior of fish schools via diffusion adaptation","authors":"Sheng-Yuan Tu, A. H. Sayed","doi":"10.1109/CIP.2010.5604109","DOIUrl":"https://doi.org/10.1109/CIP.2010.5604109","url":null,"abstract":"Fish organize themselves into schools as a way to defend against predators and improve foraging efficiency. In this work we develop a model for food foraging and explain how a school of fish can move as a group if every fish were to employ a distributed strategy, known as diffusion adaptation. The algorithm assumes the fish sense the general direction of food and can also infer the general direction of motion of their neighbors. The result indicates that a simple diffusion algorithm can account for the foraging behavior. The study also reveals that some form of communication among the fish is crucial to achieve schooling.","PeriodicalId":171474,"journal":{"name":"2010 2nd International Workshop on Cognitive Information Processing","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117204962","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}