An optimal symbol-by-symbol detection scheme for duobinary signaling (Class I PRS) which exploits the inherent correlation properties of partial response signaling (PRS) is postulated. Analytical results indicate a maximum improvement of approximately 0.7 dB over conventional split shaping duobinary detection at a 10-4error rate. Although duobinary signaling is emphasized, sufficient generality within the formulation is maintained to accommodate any class of PRS.

New results are presented for symbol-by-symbol detection with decision-directed tracking of colored channel disturbances. Recursive sampled-data algorithms are shown for Maximum A Posteriori Probability of detection under colored additive and multiplicative Gaussian noises along with white Gaussian noise. Preliminary evaluation of the algorithms via Monte Carlo simulation shows good performance compared to standard white-noise only algorithms.

Simulation results are presented for the error-rate performance of the recursive digital maximum a posteriori probability (MAP) detector for knownM-ary signals in multiplicative and additive Gaussian noise. The structure of the digital simulation of the optimum detector is generally described, with specific results obtained for a quaternary signal and 2500 digit per second transmission rate. The simulation is focused on the aeronautical multipath communication problem. Plots of detection error rate versus additive signal-to-noise ratio are given, with the power ratio of multiplicative process to desired signal as a parameter. Results are presented for the cases where the detector has perfect knowledge of the first- and second-order statistics of the multiplicative and additive processes and also where these statistics are estimated in near real time. For comparison, the error rates of conventional coherent and noncoherent digital MAP detectors are also obtained. It is shown that with nonzero multiplicative noise, the error rates of the conventional detectors saturate at a level that is irreducible for increasing additive signal-to-noise ratio. The error rate of the optimum detector having perfect statistical knowledge continues to decrease rapidly with increasing additive signal-to-noise ratio. In the absence of multiplicative noise, the conventional coherent detector and the optimum detector are shown to exhibit identical performance. Suboptimum detectors, having less than perfect statistical knowledge, yield error rates bounded below by the optimum detector rates and bounded above by the conventional detector rates.

This paper presents the derivation of the recursive algorithms necessary for real-time digital detection ofM-ary known signals that are subject to independent multiplicative and additive Gaussian noises. The motivating application is minimum probability of error detection of digital data-link messages aboard civil aircraft in the earth reflection multipath environment. For each known signal, the detector contains one Kalman filter and one probability computer. The filters estimate the multipath disturbance. The estimates and the received signal drive the probability computers. Outputs of all the computers are compared in amplitude to give the signal decision. The practicality and usefulness of the detector are extensively discussed.

One of the fundamental technical problems in aeronautical digital communications is that of multipath propagation between aircraft and ground terminal. This paper examines in detail a model of the received multipath signal that is useful for application of modern detection and estimation theories. The model treats arbitrary modulation and covers the selective and nonselective cases. The necessarily nonstationary statistics of the received signal are determined from the link geometry and the surface roughness parameters via a Kirchhoff solution. Use of the model in solving detection and estimation problems is outlined. Results of a flight experiment are presented and compared to a digital simulation for verification of the model.