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Cramer-Rao lower bound on ranging precision of pulsed laser circular-viewing detection.pdf
Optik 127 (2016) 10961–10970
Contents lists available at ScienceDirect
Optik
journal homepage: www.elsevier.de/ijleo
Cramer-Rao lower bound on ranging precision of pulsed laser circular-viewing detection
Xu Xiaobin, Zhang He ?, Chen Shanshan
School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China
article info
Article history: Received 4 July 2016 Accepted 31 August 2016
Keywords: Laser circular-viewing detection Plane characteristic Echo equation Cramer-Rao lower bounds Ranging precision
abstract
To analyze ranging precision of laser circular-viewing detection system, received Laser signal model is established, echo signal equation is derived as target is ?at surface. Based on the Cramer-Rao lower bound (CRLB) in the estimation theory, the CRLB calculation formula for estimating the variance of the range estimation with Gauss noise is derived. The effects of various parameters on the CRLB of ranging precision are analyzed by computer simulation. The results demonstrate that with the increase of tilt angle of ?at surface or decrease of diffuse re?ection, ranging precision descends. With the increase of pulse width, distance accuracy shows a trend from decline to rises.
? 2016 Elsevier GmbH. All rights reserved.
1. Introduction
Pulsed laser circular-viewing detection system has been widely used in many ?elds of imaging, laser warning and military ranging [1–6]. Pulsed laser circular-viewing detection is a mechanism with pulsed laser beam sweeping 360 ? which could measure the pulse laser round-trip time to calculate range. In the process of measurement, on account of existence of noise, the estimated range always has a certain variance [7–9]. We need a method to evaluate that variance.
In terms of basic theoretical research about ranging, Johnson and Cain studied the range accuracy of the laser radar system. They derived the Cramer-Rao lower bound of the ranging accuracy in consideration of Poisson noise distribut
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