mbining (1.88) and (1.89) gives (1.90) which is identical to (1.63) (the case of FH/QPSK in the presence of partial- band noise jamming) independent of the chip rate R The above discussion concerns the spectral characteristics of the spread tone jammer which, as concluded, resembles a white noise jammer with iden- tical spectral density. We shall now discuss the assumptions and theoretical adjustments under which the spread tone jammer can also be treated as a Gaussian noise interference. Consider an FH/PN/QPSK demodulator, similar to the one in Figure 1.2, where the despreading process now also includes a PN code correlator fol- lowing the frequency dehopper. Let p represent the PN code length (in num- ber of chips). Accounting for the effects of the spread jammer only (i.e., neglecting thermal noise), it follows that the decision variable ZI for the in- phase channel (see (1.11)) becomes (1.91) where (1.92) and c(t) is the 1-valued PN waveform. In deriving (1.91), ideal PN code synchronization at the receiver has been assumed. Recalling that the pro- cessing gain is the ratio of the PN chip rate to the data symbol rate, or equiv- alently T/T = I, then it follows that the integral in (1.92) amounts to a partial correlation of the PN code, starting from some random phase, pro- Performance of FH/PN/QPSK in the Presence of Partial-Band Multitone Jamming vided that the number I of integrated chips does not equal the code length p. Phrased differently, the conclusions to follow hold when 1 << I << p in a weaker sense when 1 << I modulo p << p). This is because, as is well known, the full-period integration of a PN code equals the constant 1/p, in which case, no randomness about CPN exists. On the other hand, when p is very large, successive code chips can be considered almost independent, iden- tically distributed 1-valued random variables, in which case the condition I << p would provide an approximate binomial distribution for the random variable CPN. The additional constraint I >> 1 then causes this binomial dis- 