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Bayesian framework and radar: On misspecified bounds and radar-communication cooperation

Publication ,  Conference
Richmond, CD; Basu, P
Published in: IEEE Workshop on Statistical Signal Processing Proceedings
August 24, 2016

The Bayesian framework is versatile as it allows for incorporation of prior knowledge or experience in making inference. The case of no prior knowledge at all is likewise seamlessly supported. The Bayesian framework is naturally suited to many fields of science and engineering including the discipline of radar design, analysis, and function. This paper will highlight recent findings on (i) Bayesian bounds under model misspecification that include the impact of using incorrect prior information, and (ii) parameter estimation for a cooperative radar-communication system.

Duke Scholars

Published In

IEEE Workshop on Statistical Signal Processing Proceedings

DOI

Publication Date

August 24, 2016

Volume

2016-August
 

Citation

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Richmond, C. D., & Basu, P. (2016). Bayesian framework and radar: On misspecified bounds and radar-communication cooperation. In IEEE Workshop on Statistical Signal Processing Proceedings (Vol. 2016-August). https://doi.org/10.1109/SSP.2016.7551792
Richmond, C. D., and P. Basu. “Bayesian framework and radar: On misspecified bounds and radar-communication cooperation.” In IEEE Workshop on Statistical Signal Processing Proceedings, Vol. 2016-August, 2016. https://doi.org/10.1109/SSP.2016.7551792.
Richmond CD, Basu P. Bayesian framework and radar: On misspecified bounds and radar-communication cooperation. In: IEEE Workshop on Statistical Signal Processing Proceedings. 2016.
Richmond, C. D., and P. Basu. “Bayesian framework and radar: On misspecified bounds and radar-communication cooperation.” IEEE Workshop on Statistical Signal Processing Proceedings, vol. 2016-August, 2016. Scopus, doi:10.1109/SSP.2016.7551792.
Richmond CD, Basu P. Bayesian framework and radar: On misspecified bounds and radar-communication cooperation. IEEE Workshop on Statistical Signal Processing Proceedings. 2016.

Published In

IEEE Workshop on Statistical Signal Processing Proceedings

DOI

Publication Date

August 24, 2016

Volume

2016-August