An important application of spread-spectrum (SS) in military communication systems is that of making the signal difficult to intercept by unauthorized receivers. Error-correction coding techniques may be employed to reduce the required input signal-to-noise ratio at the receiver, allowing the system to operate at a lower power level, hence resulting in a lower probability of interception. In the absence of error-correction coding, a specified message bit rate, transmitted signal bandwidth, and required bit-error probability at the receiver will yield a required signal-to-noise ratio for each type of spread-spectrum system. When coding is employed, a specified decoder delay time implies a specified code complexity, and can be used to determine bounds on the required receiver signal-to-noise ratio. These performance bounds are evaluated as functions of the specified parameters. In addition, one may specify a burst interference environment in that the system must operate. Presented is the evaluation of the increase in the upper bound on signal-to-noise ratio as a result of the specification of a correctable single-burst time. This increase indicates an antiintercept /antijam tradeoff.

Upper bounds are presented on the size of equal energy continuous time signal sets occupying a given time-bandwidth (TB) product under specified synchronous correlation constraints. Both time-limited (aperiodic) and periodic signal sets are addressed, with appropriate measures of bandwidth for each. Signal set construction techniques are derived which illustrate that the bounds for periodic signal sets are relatively tight, while those obtained for aperiodic signal sets are tight under certain conditions.

An analysis of the effect of multiple narrow-band interfering signals on the probability of error in a frequency-hopped differential phase shift keyed (FH-DPSK) spread-spectrum communication system with a nonlinear receiver is given. In this analysis it is assumed that the sum of the outputs from ann-subchannel receiver is a Gaussian random variable. Subject to this assumption, numerical evaluations of the probability of error for both nonfading and Rayleigh fading channels are presented and compared with those of a linear receiver. The results indicate that the performance of a nonlinear receiver is better than that of a linear receiver for any signal-to-interference ratio.

The autoregressive (AR) spectral estimator is used to make high resolution spectral estimates based on short data records. Measures of a frequency averaged normalized bias and normalized variance of the spectral estimates are introduced. A large number of spectra are generated. Based on the above mentioned measures and visual inspection of the estimates of the generated spectra, the AR and the conventional tapered and transformed (TT) spectral estimates are compared. It is shown that the AR spectral estimator is as stable as that given by its asymptotic variance. It is also shown that the AR spectral estimator is most powerful in estimating narrow spectral peaks with a high signal-to-interference ratio in the signal bandwidth.

A basic signal design problem which arises in the construction of aperiodic signals with good correlation properties is how small can the peak value of the cross-correlation function be when the signals occupy approximately the same frequency spectra. The authors are not aware of any published results on this problem prior to Anderson's work (in preparation). He derives a lower bound on the maximum in ν of the rms value of the convolution of f(x)eiνxand g(x) where f and g are square integrable functions, the lower bound being expressed in terms of the energy bandwidth of f and g. In this correspondence, these results are used to obtain a lower bound on the maximum in τ and ν of the envelope of the crosscorrelation function between two real, bandpass, time-limited signals when one is frequency shifted by ν, assuming that the signals are in the same passband. The lower bound is expressed in terms of a notion of ϵ-approximete energy bandwidth. By using a similar approach, and defining a bandwidth measure given by Zakai (1960) a different lower bound is obtained. Furthermore, this approach yields an upper and lower bound on the rms value of the envelope of the cross-correlation function. For the special case when the signals have identical energy spectral densities, the rms value of the envelope of the cross-correlation function is related to the timebandwidth product of the signals and is independent of the phase characteristics of their Fourier transforms.