Analysis of Internally Bandlimited Multistage Cubic-Term Generators for RF Receivers

Adaptive feedforward error cancellation applied to correct distortion arising from third-order nonlinearities in RF receivers requires low-noise low-power reference cubic nonidealities. Multistage cubic-term generators utilizing cascaded nonlinear operations are ideal in this regard, but the frequency response of the interstage circuitry can introduce errors into the cubing operation. In this paper, an overview of the use of cubic-term generators in receivers relative to other applications is presented. An interstage frequency response plan is presented for a receiver cubic-term generator and is shown to function for arbitrary three-signal third-order intermodulation generation. The noise of such circuits is also considered and is shown to depend on the total incoming signal power across a particular frequency band. Finally, the effects of the interstage group delay are quantified in the context of a relevant communication standard requirement

Digital receiver study and implementation

Computer software was developed which makes it possible to use any general purpose computer with A/D conversion capability as a PSK receiver for low data rate telemetry processing. Carrier tracking, bit synchronization, and matched filter detection are all performed digitally. To aid in the implementation of optimum computer processors, a study of general digital processing techniques was performed which emphasized various techniques for digitizing general analog systems. In particular, the phase-locked loop was extensively analyzed as a typical non-linear communication element. Bayesian estimation techniques for PSK demodulation were studied. A hardware implementation of the digital Costas loop was developed

Signal-to-noise ratio estimation in digital computer simulation of lowpass and bandpass systems with applications to analog and digital communications, volume 3

Techniques are developed to estimate power gain, delay, signal-to-noise ratio, and mean square error in digital computer simulations of lowpass and bandpass systems. The techniques are applied to analog and digital communications. The signal-to-noise ratio estimates are shown to be maximum likelihood estimates in additive white Gaussian noise. The methods are seen to be especially useful for digital communication systems where the mapping from the signal-to-noise ratio to the error probability can be obtained. Simulation results show the techniques developed to be accurate and quite versatile in evaluating the performance of many systems through digital computer simulation

Advanced detection, isolation, and accommodation of sensor failures in turbofan engines: Real-time microcomputer implementation

The objective of the Advanced Detection, Isolation, and Accommodation Program is to improve the overall demonstrated reliability of digital electronic control systems for turbine engines. For this purpose, an algorithm was developed which detects, isolates, and accommodates sensor failures by using analytical redundancy. The performance of this algorithm was evaluated on a real time engine simulation and was demonstrated on a full scale F100 turbofan engine. The real time implementation of the algorithm is described. The implementation used state-of-the-art microprocessor hardware and software, including parallel processing and high order language programming

Automatic programming methodologies for electronic hardware fault monitoring

This paper presents three variants of Genetic Programming (GP) approaches for intelligent online performance monitoring of electronic circuits and systems. Reliability modeling of electronic circuits can be best performed by the Stressor - susceptibility interaction model. A circuit or a system is considered to be failed once the stressor has exceeded the susceptibility limits. For on-line prediction, validated stressor vectors may be obtained by direct measurements or sensors, which after pre-processing and standardization are fed into the GP models. Empirical results are compared with artificial neural networks trained using backpropagation algorithm and classification and regression trees. The performance of the proposed method is evaluated by comparing the experiment results with the actual failure model values. The developed model reveals that GP could play an important role for future fault monitoring systems.This research was supported by the International Joint Research Grant of the IITA (Institute of Information Technology Assessment) foreign professor invitation program of the MIC (Ministry of Information and Communication), Korea

Synthesis methods for manual aerospace control systems with applications to SST design

Synthesis methods for manual aerospace control systems using digital programming and man machine performance data with application to supersonic transport desig

Design study of a device to simulate the dynamic environment encountered under condi- tions of reduced or zero gravity final report

Design study of reduced or zero gravity environment simulation devic