Výsledky vyhledávání

Jammer robust model-aided deep learning-based target detection for cognitive sonar

Publikováno v: The Journal of the Acoustical Society of America. 152:A243-A243

This work extends the development of an adaptive deep learning-based target detection algorithm for a channel matrix-based cognitive sonar framework that makes use of both a primary and secondary dataset. The channel matrix-based framework models all

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3274713079130f1b11e76ff157e21a09
https://doi.org/10.1121/10.0016149

Zobrazit plný text záznamu

Optimal Target Detection for Random Channel Matrix-Based Cognitive Radar/Sonar

Autor: Christ D. Richmond, Touseef Ali

Publikováno v: 2021 IEEE Radar Conference (RadarConf21).

Conventional techniques for characterizing clutter depend on covariance-based statistical modeling. This presents a disadvantage to cognitive radar/sonar since optimizing waveform design becomes highly nonconvex. Modeling the clutter and target respo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b5fcbd7cb999023c59e2a97cf31d36b6
https://doi.org/10.1109/radarconf2147009.2021.9455266

Zobrazit plný text záznamu

Bounds on Bearing, Symbol, and Channel Estimation Under Model Misspecification

Autor: Touseef Ali, Christ D. Richmond, Akshay S. Bondre

Publikováno v: ACSSC

The constrained Cramer-Rao bound (CRB) has been used successfully to study parameter estimation in flat-fading scenarios, and established the value of side information such as known waveform properties (e.g. constant modulus) and known training symbo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::fdad9239896ac543c3e479e3d9199a8c
https://doi.org/10.1109/ieeeconf51394.2020.9443488

Zobrazit plný text záznamu

On Wilks' Theorem for Generalized Likelihood Ratio Test Performance of Cooperative Radar-Communications

Autor: Christ D. Richmond, Touseef Ali, Akshay S. Bondre

Publikováno v: 2020 IEEE Radar Conference (RadarConf20).

The analysis of the generalized likelihood ratio test (GLRT) radar receiver when the radar is coexisting with a cooperative in-band communication (comm.) system is challenged by the discrete nature of the comm. symbols. While the asymptotic performan

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::aa03e9ad75970352cc32c997ffeeff66
https://doi.org/10.1109/radarconf2043947.2020.9266344

Zobrazit plný text záznamu

Model-aided deep learning-based target detection for channel matrix-based cognitive radar/sonar

Autor: Touseef Ali, Akshay S. Bondre, Christ D. Richmond

Publikováno v: The Journal of the Acoustical Society of America. 151:A100-A100

Data driven based approaches to signal processing including deep neural networks (DNN) have shown promise in various fields. Such techniques tend to require significant training for good convergence. Model-based approaches, however, provide practical

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::073b58ead2385ccad79b806a250a26ef
https://doi.org/10.1121/10.0010784

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání