RT_Pcfar

(rtools/RT_Pcfar.m)

Function Synopsis

val = bin(top, bot)

Help text

function P = RT_Pcfar(T, N, S, model, k1, k2)

 Given a linear threshold T, returns the CFAR probability
 for the following models:
 CA   - Cell Average
 CAGO - Cell Average Greatest Of
 CASO - Cell Average Smallest Of
 OS   - Order Statistic (k1th largest)
 TM   - Trimmed Mean (k1 smallest & k2 largest trimmed)

 The threshold T is based on the test statistic Z, and
 underlying normalised Gaussian statistics (i.e. the
 distribution is exponential in intensity and of unity mean)
 see RT_cfar.m for definitions of Z according to [1].

 For a total background window size N (=even number).
 Using S = 0 returns the Probability of False Alarm.
 Use RT_Tcfar.m to invert for threshold T from probability P.

 Passing a linear target strength S > 0 returns
  the Probability of Detection for a Swerling 1 target.

 T can be an array if size is compatible with S.

 Source:
  [1] `Analysis of CFAR Processors in Nonhomogeneous
   Background', P.P.Gandhi and S.A.Kassam, IEEE Trans. AES,
   24(4), July 1988, pp 427-445
  [2] `Detection performance of the trimmed-mean CFAR
   processor with noncoherent integration', M.B. El Mashade,
   IEE Proc. Radar, Sonar and Navigation, 142(1), Feb 1995, pp 18-24

 Part of the Matlab Radar Toolbox v0.11 by Glen Davidson at www.radarworks.com
 Please acknowledge use of this toolbox in any publication or software.
 This header must be retained in any derivative work

Cross-Reference Information

RT_Tcfar                      rtools/RT_Tcfar.m
cfar_theory_demo              rtools/cfar_theory_demo.m