volutional, and concatenated codes for FH/MFSK sys- tems in partial-band noise [2], [14]-[16]. Of these, the paper by Ma and Poole [16] is perhaps the most comprehensive. In this section, we will consider mul- titone as well as partial-band noise jamming. This is important since we have previously seen that n = 1 band multitone jamming is the most effective type of interference against uncoded FH/MFSK signals, with or without diversity, Coding Countermeasures for K > 2. It will also provide some insights into the effect of the jamming channel characteristics on the performance of some of the more popular codes in use today. Our intention is not to exhaustively analyze the performance of every known code in all types of jamming. The emphasis will be on providing the analytical tools for evaluating the effectiveness of coding against worst case FH/MFSK jammers. Specifically, we will consider several binary and M-ary convolutional codes, Reed-Solomon codes (because their burst error cor- rection capabilities make them attractive for non-stationary interference), and concatenated schemes employing Reed-Solomon outer codes and con- volutional inner codes. With regard to jamming categories, we will restrict our analysis to partial-band noise and n = 1 band multitone jamming. The detection metric remains the unweighted linear combination of received chip energies, with perfect jamming state side information. We will be concerned with the relative performance of these codes in worst case jamming, and how they compare with the unsophisticated repetition codes with optimum diver- sity previously analyzed. 2.3.2.1 Convolutional Codes Our analytical approach mirrors that of Chapter 4, Part 1, and [8]. Simulation techniques aside, most coding performance analyses are based on bounds of the form (see (4.24), Volume I) Pb ( G(D) (2.130) where the structure of G(D) depends only on the coder and decoder char- acteristics, while the parameter D is separably dependent only on the type of jamming and the detection metric. In particu