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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Vol. 10, Iss. 5 — May. 1, 1971
  • pp: 1051–1056

Calibration, Precision, and Efficiency of Optical Range Finders

S. Ackerman  »View Author Affiliations


Applied Optics, Vol. 10, Issue 5, pp. 1051-1056 (1971)
http://dx.doi.org/10.1364/AO.10.001051


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Abstract

Properties of pulsed optical range finders which are affected by the transmitter pulse waveshape have been analyzed. This was done by deriving the probability density functions of the random variable representing range delay time with respect to the start of the transmitter pulse. These functions were used to predict the calibration or bias time, random range errors, the probability that a range measurement is made, and its entropy, all vs signal energy. Noise and other important system properties are treated as parameters, and it is assumed that photoemission is Poisson-distributed. A number of experiments were performed, including a simulation of geodetic satellite conditions. Although more experimental work remains to be done, the agreement between these measurements and theoretical predictions tends to verify the theory, including the basic assumption that photoemission is accurately described by Poisson statistics under almost all likely conditions.

© 1971 Optical Society of America

History
Original Manuscript: September 22, 1970
Published: May 1, 1971

Citation
S. Ackerman, "Calibration, Precision, and Efficiency of Optical Range Finders," Appl. Opt. 10, 1051-1056 (1971)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-10-5-1051


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References

  1. L. Mandel, Proc. Phys. Soc. 72, 1037 (1958). [CrossRef]
  2. All sets describing first detection at the Ith interval of δ [Eqs. (3) and (4)].
  3. E. Parzen, Modern Probability Theory and Its Applications, (Wiley, New York, 1960), Chap. 5.
  4. G. Raisbeck, Information Theory (MIT Press, Cambridge, 1964), Chap. 1.
  5. The sampling theorem may be invoked to see how the larger number of measurements can be converted into more statistically independent range tracks and these, in turn, averaged to reduce random error.

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