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The '''K-distribution''' is a [[probability distribution]] that arises as the consequence of a statistical or probabilistic model used in [[Synthetic aperture radar|Synthetic Aperture Radar]] (SAR) imagery. The K distribution is formed by [[Compound probability distribution|compounding]] two separate [[probability distribution]]s, one representing the [[radar cross-section]], and the other representing speckle that is a characteristic of coherent imaging.


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The model used to represent the observed intensity ''X'', involves compounding two [[gamma distribution]]s. In each case a reparameterisation of the usual form of the family of gamma distributions is used, such that the parameters are:
:*the mean of the distribution, and
:*the usual shape parameter.
 
==Density==
The model is that ''X'' has a gamma distribution with mean ''σ'' and shape parameter ''L'', with ''σ'' being treated as a [[random variable]] having another gamma distribution, this time with mean ''μ'' and shape parameter ''ν''. The result is that ''X'' has the following density function (''x''&nbsp;>&nbsp;0):<ref name=Redding>Redding (1999)</ref>
 
:<math>f_X(x;\nu,L)= \frac{2}{x} \left( \frac{L \nu x}{\mu} \right)^\frac{L+\nu}{2}
      \frac{1}{\Gamma(L)\Gamma(\nu)}
      K_{\nu-L} \left( 2 \sqrt{\frac{L \nu x}{\mu} } \right), </math>
 
where ''K'' is a [[modified Bessel function]] of the second kind. In this derivation, the K-distribution is a [[compound probability distribution]]. It is also a [[product distribution]]:<ref name=Redding/> it is the distribution of the product of two independent random variables, one having a gamma distribution with mean 1 and shape parameter ''L'', the second having a gamma distribution with mean ''μ'' and shape parameter ''ν''.
 
This distribution derives from a paper by Jakeman and Pusey (1978).
 
==Moments==
The mean and variance are given<ref name=Redding>Redding (1999)</ref> by
:<math> \operatorname{E}(X)= \mu </math>
:<math> \operatorname{var}(X)= \mu^2 \frac{ \nu+L+1}{L \nu} .</math>
 
==Other properties==
All the properties of the distribution are symmetric in ''L'' and ''ν''.<ref name=Redding/>
 
==Notes==
{{Reflist}}
 
==Sources==
*Redding, Nicholas J. (1999) ''Estimating the Parameters of the K Distribution in the Intensity Domain''  [http://oai.dtic.mil/oai/oai?verb=getRecord&metadataPrefix=html&identifier=ADA368069]. Report DSTO-TR-0839, DSTO Electronics and Surveillance Laboratory, South Australia. p.&nbsp;60
*Jakeman, E.  and Pusey, P. N. (1978) "Significance of K-Distributions in Scattering Experiments", ''Physical Review Letters'', 40, 546&ndash;550  {{doi|10.1103/PhysRevLett.40.546}}
 
==Further reading==
*Jakeman, E. (1980) "On the statistics of K-distributed noise", Journal of Physics A: Mathematics and General, 13, 31&ndash;48
*Ward, K.D.; Tough, Robert J.A; Watts, Simon (2006) '' Sea Clutter: Scattering, the K Distribution and Radar Performance'', Institution of Engineering and Technology. ISBN 0-86341-503-2
{{ProbDistributions|continuous-semi-infinite}}
{{DEFAULTSORT:K-Distribution}}
[[Category:Radar signal processing]]
[[Category:Continuous distributions]]
[[Category:Compound distributions]]
[[Category:Probability distributions]]

Revision as of 14:40, 22 December 2013

The K-distribution is a probability distribution that arises as the consequence of a statistical or probabilistic model used in Synthetic Aperture Radar (SAR) imagery. The K distribution is formed by compounding two separate probability distributions, one representing the radar cross-section, and the other representing speckle that is a characteristic of coherent imaging.

The model used to represent the observed intensity X, involves compounding two gamma distributions. In each case a reparameterisation of the usual form of the family of gamma distributions is used, such that the parameters are:

  • the mean of the distribution, and
  • the usual shape parameter.

Density

The model is that X has a gamma distribution with mean σ and shape parameter L, with σ being treated as a random variable having another gamma distribution, this time with mean μ and shape parameter ν. The result is that X has the following density function (x > 0):[1]

fX(x;ν,L)=2x(Lνxμ)L+ν21Γ(L)Γ(ν)KνL(2Lνxμ),

where K is a modified Bessel function of the second kind. In this derivation, the K-distribution is a compound probability distribution. It is also a product distribution:[1] it is the distribution of the product of two independent random variables, one having a gamma distribution with mean 1 and shape parameter L, the second having a gamma distribution with mean μ and shape parameter ν.

This distribution derives from a paper by Jakeman and Pusey (1978).

Moments

The mean and variance are given[1] by

E(X)=μ
var(X)=μ2ν+L+1Lν.

Other properties

All the properties of the distribution are symmetric in L and ν.[1]

Notes

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Sources

  • Redding, Nicholas J. (1999) Estimating the Parameters of the K Distribution in the Intensity Domain [1]. Report DSTO-TR-0839, DSTO Electronics and Surveillance Laboratory, South Australia. p. 60
  • Jakeman, E. and Pusey, P. N. (1978) "Significance of K-Distributions in Scattering Experiments", Physical Review Letters, 40, 546–550 21 year-old Glazier James Grippo from Edam, enjoys hang gliding, industrial property developers in singapore developers in singapore and camping. Finds the entire world an motivating place we have spent 4 months at Alejandro de Humboldt National Park.

Further reading

  • Jakeman, E. (1980) "On the statistics of K-distributed noise", Journal of Physics A: Mathematics and General, 13, 31–48
  • Ward, K.D.; Tough, Robert J.A; Watts, Simon (2006) Sea Clutter: Scattering, the K Distribution and Radar Performance, Institution of Engineering and Technology. ISBN 0-86341-503-2

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  1. 1.0 1.1 1.2 1.3 Redding (1999)