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Design and Implementation of a Communications System Using Chaotic Transmissions That Operates Over a Noisy Channel at Significant Distances, 10-9134 Printer Friendly VersionPrincipal Investigator Inclusive Dates: 04/01/99 - 10/31/00 Background - Secure communications systems would benefit from modulation, encryption, and encoding using nonlinear chaotic signals because chaotic processes exhibit several natural characteristics beneficial to communications systems. Two key features of chaos are a noise-like time series and sensitive dependence on initial conditions, which cause chaotic transmissions to have low probability of detection as an information-bearing signal and low probability of intercept, respectively. A fundamental limitation, however, is the sensitivity of the chaotic processes to amplitude, which has historically severely restricted the distance over which chaos-based systems can communicate. This limitation has previously restricted chaotic communications to a laboratory curiosity. Approach - The main purpose of this project was to develop an approach that overcomes the extreme sensitivity of chaos-based receivers to received signal amplitude. This approach was primarily developed by investigation, system design, and performance evaluation via modeling and simulation because chaos is not well suited to mathematical analytical methods. It was further desired to develop a hardware demonstration of the resulting system to substantiate fully the viability of fielding chaotic communications systems. This secondary goal required an initial conversion of the algorithms from the high-level mathematics language in which they were developed to the ubiquitous C programming language. The C-code could then be passed through a software translator to generate assembly language for a digital signal-processing (DSP) chip. Accomplishments - A hardware demonstration was constructed to physically prove the viability of chaos as a tool for secure communications. Chaotic communication was shown to be possible over arbitrary attenuation, verifying the solution of the distance problem and thrusting chaos into the realm of realizable communications technology. The most significant problem solved was the sensitivity of chaotic receivers to amplitude variation by a digital signal-processing algorithm called the Signal Amplitude Restorer. The chaotic receiver with uncorrected signal levels lost synchronization at ±3-decibels signal level variation, while the augmented receiver retained synchronization at all levels between ±200 decibels. It is interesting to compare a chaotic waveform with an equivalent direct sequence spread spectrum (DSSS) waveform, which is the current standard for LPD noise-like waveforms. The top graph below illustrates an actual chaotic signal in time (top) and frequency (bottom), while the bottom graph shows the equivalent actual DSSS time and frequency traces. It is obvious that the DSSS time signal is highly structured and capable of carrying information. In addition, immediate intelligence can be gathered from an intercepted signal in the form of chipping sequence reconstruction because there is a direct relationship between logical state (0 or 1) and transmitted voltage (-1 or +1, respectively). The chaotic waveform, on the other hand, has no obvious structure. It looks like a noise signal incapable of information transference. It has similar spectrum-spreading capability, as seen by the similarities in the frequency traces. In addition, it is a fundamentally more secure signal because there is no direct relationship between logical state (0 or 1) and transmitted voltage; all values in the range ±1.285 will be sent for either logical state. No intelligence is immediately discernible, making chaos a significantly more secure signal than spread spectrum. Possible applications include
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