Accuracy of linear multiple-input multiple-output (MIMO) models obtained by maximum likelihood estimation

Automatica ◽  
2012 ◽  
Vol 48 (4) ◽  
pp. 632-637 ◽  
Author(s):  
Juan C. Agüero ◽  
Cristian R. Rojas ◽  
Håkan Hjalmarsson ◽  
Graham C. Goodwin
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Multiple Input Multiple Output ◽  
Likelihood Estimation ◽  
Multiple Input ◽  
Input Multiple Output

scholarly journals Novel Methods for Approximate Maximum Likelihood Estimation of Multiple Superimposed Undamped Tones and Their Application to Radar Systems

2021 ◽  
Author(s):  
Pasquale Di Viesti ◽  
ALESSANDRO DAVOLI ◽  
Giorgio Guerzoni ◽  
Giorgio Matteo Vitetta
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Multiple Input Multiple Output ◽  
Likelihood Estimation ◽  
Approximate Maximum Likelihood ◽  
Radar Systems ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Novel Methods

<div>In this manuscript, novel methods for the detection of multiple superimposed tones in noise and the estimation of their parameters are derived, and their application to colocated multiple-input multiple-output radar systems is investigated.</div>

scholarly journals Novel Methods for Approximate Maximum Likelihood Estimation of Multiple Superimposed Undamped Tones and Their Application to Radar Systems

2021 ◽  
Author(s):  
Pasquale Di Viesti ◽  
ALESSANDRO DAVOLI ◽  
Giorgio Guerzoni ◽  
Giorgio Matteo Vitetta
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Multiple Input Multiple Output ◽  
Likelihood Estimation ◽  
Approximate Maximum Likelihood ◽  
Radar Systems ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Novel Methods

<div>In this manuscript, novel methods for the detection of multiple superimposed tones in noise and the estimation of their parameters are derived, and their application to colocated multiple-input multiple-output radar systems is investigated.</div>

scholarly journals Novel Methods for Approximate Maximum Likelihood Estimation of Multiple Superimposed Undamped Tones and Their Application to Radar Systems

2021 ◽  
Author(s):  
Pasquale Di Viesti ◽  
ALESSANDRO DAVOLI ◽  
Giorgio Guerzoni ◽  
Giorgio Matteo Vitetta
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Multiple Input Multiple Output ◽  
Likelihood Estimation ◽  
Approximate Maximum Likelihood ◽  
Radar Systems ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Novel Methods

<div>In this manuscript, novel methods for the detection of multiple superimposed tones in noise and the estimation of their parameters are derived, and their application to colocated multiple-input multiple-output radar systems is investigated.</div>

MIMO Radar Target Detection Performance Analysis with Unknown Parameters

2011 ◽  
Vol 403-408 ◽  
pp. 182-186
Author(s):  
Wei Wei Liu ◽  
Ning Cao ◽  
Hao Lu ◽  
Ju Rong Hu
Keyword(s):  
Performance Analysis ◽  
Multiple Input Multiple Output ◽  
Likelihood Estimation ◽  
Mimo Radar ◽  
Low Rank ◽  
Radar Target ◽  
Signal Power ◽  
Unknown Parameters ◽  
Multiple Input ◽  
Input Multiple Output

Motivated by the development of Multiple-Input Multiple-Output (MIMO) communication, MIMO radar has drawn considerable attention. While, to design of MIMO radar detector, transmitting signal power and noise are usually assumed known in advance, but in practice we may need to estimate the transmitting signal power and noise first. In this paper, we introduce MIMO radar target performance analysis with unknown parameters. First transmitting signal energy is estimated by Maximum likelihood Estimation(MLE) when multipath satisfy special diversity condition and multipath has low rank. Then the detector in the Neyman-Pearson is developed and analyzed with estimated parameters. The simulation results show that the performance with unknown parameters is approximate to the detector with known parameters. The method proposed in this paper can be used to design the MIMO radar detectors with unknown parameters.

scholarly journals MIMO Detectors Under Correlated Channels

2016 ◽  
Vol 37 (1) ◽  
pp. 3
Author(s):  
Bruno Felipe Costa ◽  
Alex Miyamoto Mussi ◽  
Taufik Abrão
Keyword(s):  
Maximum Likelihood ◽  
Interference Cancellation ◽  
Mean Squared Error ◽  
Multiple Input Multiple Output ◽  
Successive Interference Cancellation ◽  
Correlated Channels ◽  
Minimum Mean Squared Error ◽  
Squared Error ◽  
Multiple Input ◽  
Input Multiple Output

Este artigo analisa o desempenho de detectores com múltiplas antenas transmissoras e múltiplas antenas receptoras (MIMO – multiple-input multiple-output) em canais com desvanecimento correlacionados. Dois esquemas de detecção MIMO denominados erro quadrático médio mínimo (MMSE – minimum mean squared error) – com ou sem a etapa de cancelamento de interferência sucessiva ordenado (OSIC – ordered successive interference cancellation) – e técnica de redução treliça (LR – lattice reduction) são analisados e comparados com o limite de detecção de máxima verossimilhança (ML – maximum likelihood) em cenários específicos de interesse: (a) com incremento da eficiência espectral através do aumento do número de antenas. (b) quando há aumento nos índices de correlação de desvanecimento do canal. Neste contexto, o desempenho do detector ótimo ML-MIMO é utilizado como referência visando caracterizar o comportamento da taxa de erro de bit (BER) destes detectores MIMO e quão próximo esses estão do desempenho ML-MIMO.

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