SNR lidar signal improovement by adaptive tecniques

were P(t) is lidar observation after deconvolution process, strongly dependent on geometrical and optical characteristics of the sensor, and Pδ(t) is ideal observation when the response funtion of lidar sensor is a Diràc distribution, like ideal laser pulse. From (1), the additive noise term N(t) makes a direct deconvolution impossible. In general, deconvolution process with R(t) show a low-pass characteristic, and this operation intensifies the range of higher frequencies, were N(t) contributions are relevant. Consequently a pre-low-pass filtering of observed data can be very useful in some cases. The aim of this paper is to propose a new filtering scheme whit an Adaptive Noise Canceller (ANC), that with knowing of a-priori noise statistic and lidar prifile, optimeze a set of digital filter coefficients to adapt its impulse response to improove SNR. The choice for adaptive algorithm in an N-LMS (Normalized-Least Mean Square) that update filter weight looking-up to input signal power, making a fine tuning of impulse response.