lly dom- inant jamming power. We will consider the two principal types of intelligent but non-adaptive FH jamming threats, namely, partial-band noise and multitone interference. It will be shown that when such jammers optimize their system parameters based on their assumed knowledge of the FH/MFSK target, the resulting performance degradation can be severe, particularly at low error probabil- ities. To counteract this threat, the FH system must incorporate some cod- ing redundancy which allows the received data decisions to be based on multiple hops. One particularly simple coding scheme that we will consider is time diversity or repetition coding, which can also be used in a concate- Broadband Noise Jamming nation struture to augment the effectiveness of the more powerful block and convolutional codes. In analyzing these coded systems, we will focus on a detection metric that assumes that the receiver can determine with certainty whether a given hop is jammed. This is the so-called perfect jamming state knowledge or side- information case discussed in Chapters 3 and 4, Part 1, and it is a common assumption in many published articles on pulsed jamming of DS systems and the dual case of partial-band jamming of FH systems (e.g., [2, p. 288]). However, we should caution that in practice a receiver's derived jamming state side information is subject to error, and such a metric is non-robust in the sense that it depends on the received signal, thermal noise, and jamming power levels. While a few other, more robust metrics are considered at the end of this chapter, our main intent here is not to exhaustively consider all possible detection metrics, but rather to use the principal selected metric to illustrate techniques for analyzing the performance of a variety of coded FH/MFSK systems in the presence of different jamming strategies. We will also not consider the class of adaptive jammers known as repeat- back or frequency-follower jammers. As technology moves to higher hop rates, this threat becomes less viable since