دورية أكاديمية

Regularized Tapered Sample Covariance Matrix

التفاصيل البيبلوغرافية
العنوان: Regularized Tapered Sample Covariance Matrix
المؤلفون: Ollila, Esa, Breloy, Arnaud
المساهمون: Laboratoire Energétique Mécanique Electromagnétisme (LEME), Université Paris Nanterre (UPN)
المصدر: ISSN: 1053-587X ; IEEE Transactions on Signal Processing ; https://hal.science/hal-04313499Test ; IEEE Transactions on Signal Processing, 2022, 70, pp.2306-2320. ⟨10.1109/TSP.2022.3169269⟩.
بيانات النشر: HAL CCSD
Institute of Electrical and Electronics Engineers
سنة النشر: 2022
المجموعة: Université Paris Lumières: HAL
مصطلحات موضوعية: sample covariance matrix shrinkage regularization elliptically symmetric distributions tapering banding sphericity, sample covariance matrix, shrinkage, regularization, elliptically symmetric distributions, tapering, banding, sphericity, [STAT]Statistics [stat]
الوصف: International audience ; Covariance matrix tapers have a long history in signal processing and related fields. Examples of applications include autoregressive models (promoting a banded structure) or beamforming (widening the spectral null width associated with an interferer). In this paper, the focus is on high-dimensional setting where the dimension p is high, while the data aspect ratio n/p is low. We propose an estimator called TABASCO (TApered or BAnded Shrinkage COvariance matrix) that shrinks the tapered sample covariance matrix towards a scaled identity matrix. We derive optimal and estimated (data adaptive) regularization parameters that are designed to minimize the mean squared error (MSE) between the proposed shrinkage estimator and the true covariance matrix. These parameters are derived under the general assumption that the data is sampled from an unspecified elliptically symmetric distribution with finite 4th order moments (both real-and complex-valued cases are addressed). Simulation studies show that the proposed TABASCO outperforms all competing tapering covariance matrix estimators in diverse setups. An application to space-time adaptive processing (STAP) also illustrates the benefit of the proposed estimator in a practical signal processing setup.
نوع الوثيقة: article in journal/newspaper
اللغة: English
العلاقة: hal-04313499; https://hal.science/hal-04313499Test; https://hal.science/hal-04313499/documentTest; https://hal.science/hal-04313499/file/J20_TSP22.pdfTest
DOI: 10.1109/TSP.2022.3169269
الإتاحة: https://doi.org/10.1109/TSP.2022.3169269Test
https://hal.science/hal-04313499Test
https://hal.science/hal-04313499/documentTest
https://hal.science/hal-04313499/file/J20_TSP22.pdfTest
حقوق: info:eu-repo/semantics/OpenAccess
رقم الانضمام: edsbas.33E47960
قاعدة البيانات: BASE