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

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.