Estimação de posição e velocidade de um alvo com base em TDOA e FDOA em sistemas de radar passivo usando redes neurais feedforward

Bruno Pompeo, Daniel Nicolalde Rodríguez, José Antonio Apolinário Jr., Marcelo Campos, Wallace Alves Martins

DOI: 10.14209/sbrt.2022.1570823738

Evento: XL Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2022)

Keywords: passive radar feedforward neural network time difference of arrival frequency difference of arrival

Abstract

In this paper, the authors investigate the use of feedforward neural networks to estimate the location and velocity of non-cooperative targets in passive radar systems. Time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements between the direct-path signals originated by an illuminator of opportunity and the target's reflected signals acquired by sensors are the possible network inputs. Concerning network inputs, simulated experiments use only TDOAs, only FDOAs, or both measurements. Furthermore, to determine efficient network parameters, the experiments vary the number of neurons, amount of receivers, and error degrees. Finally, the best network results are compared with other estimation techniques.

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