RT_Tcfar

(rtools/RT_Tcfar.m)

Function Synopsis

T = RT_Tcfar(P, N, S, model, k1, k2, trace)

Help text

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

 Given a scalar probability P, returns the CFAR threshold T
 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 Target Free Threshold (where
  P refers to probability of False Alarm)
 Use RT_Pcfar.m to obtain probability P from threshold T.

 Passing a linear target strength S > 0 returns
  the Target Threshold for a Swerling 1 target (where
  P refers to probability of Detection)

 Set trace to follow the numerical search

 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_Pcfar                      rtools/RT_Pcfar.m

cfar_sim_demo                 rtools/cfar_sim_demo.m
cfar_theory_demo              rtools/cfar_theory_demo.m