This book is about aerospace sensors, their principles of operation, and their typical advantages, shortcomings, and vulnerabilities. They are described in the framework of the subsystems where they function and in accordance with the flight mission they are designed to serve. The book is intended for students at the advanced undergraduate or graduate level and for research engineers who need to acquire this kind of knowledge. An effort has been made to explain, within a uniform framework of mathematical modeling, the physics upon which a certain sensor concept is based, its construction, its dynamics, and its error sources and their corresponding mathematical models. Equipped with such knowledge and understanding, the student or research engineer should be able to get involved in research and development activities of guidance, control, and navigation systems and to contribute to the initiation of novel ideas in the aerospace sensor field. As a designer and systems engineer, he should be able to correctly interpret the various items in a technical data list and thus to interact intelligently with manufacturers' representatives and other members of an R&D team. Much of the text has evolved from undergraduate and graduate courses given by the author during the past seventeen years at the Department of Aerospace Engineering at the Technion- Israel Institute of Technology and from his earlier research and development experience in flight control, guidance, navigation, and avionics at the Ministry of Defense Central Research Institute.
and historical background.- 1. Principles and Elements of Measurement Systems.- 1.0 Introduction.- 1.1 Elements in open-loop instruments.- Instruments, sensors, and systems.- Basic sensor elements.- Auxiliary functions and elements.- Equilibrium.- Definitions of sensor functions.- 1.2 Measures and units.- Basic measures.- Units and standards.- Reference values.- 1.3 Passive and active instruments.- Contact and remote sensing.- Tapping of energy sources.- Input impedance.- 1.4 Characteristics, resolution, and dynamic range.- Domain and range.- Linearity, resolution, and dynamic range.- Bias, dead zone, and saturation.- Hysteresis.- 1.5 Errors due to dynamics, nonlinearity, and noise.- System and measurement equations.- Classification of errors.- 1.6 Environmental interference.- Error model formulation.- Additive and scaling errors.- 1.7 Error compensation.- Isolation and protection.- Output compensation.- Input compensation.- 1.8 Estimation of characteristics by regression.- Error modeling.- Linear regression.- Precision of the estimate.- 1.9 Deflection instruments.- Excitation, response, and display.- Basic tradeoffs.- The role of the restoring force.- 1.10 Balancing instruments.- The force balance principle.- Linearization by forced balance.- The effect of additive noise.- Sensitivity to variations in parameters.- 1.11 Imperfections and limitations on precision.- Sensor dynamics and design parameter tradeoffs.- Performance parameters and further design tradeoffs.- Enhancement of bandwidth.- Considerations of bandwidth, dynamic range, and robustness.- 1.12 Effect of friction in instrument servomechanisms.- Linear model of DC motor.- The linear motor model including friction.- Effect of loop closure on minimum speed.- Problems.- References.- 2. Random Processes and Signals.- 2.0 Introduction.- 2.1 Statistical characterization of random variables.- Time averages of sample functions.- 2.2 Ensemble averages of sample functions.- Ensemble of sample functions.- The probability density function.- Expectation.- Generalized moments.- Stationarity.- Power and variance.- 2.3 Joint distribution, correlation.- Correlation.- Orthogonality.- The distribution law.- Autocorrelation.- 2.4 Correlation coefficient and functions.- The correlation coefficient.- The autocorrelation function.- The cross-correlation function.- 2.5 Time and ensemble averages, ergodicity.- Conditions for equivalence of time and ensemble averages.- Ergodicity.- 2.6 Mathematical operations on random processes.- Autocorrelation of the sum of random functions.- Cross-correlation between a random function and its time derivatives ?.- Filtering of white noise, Markov processes.- Further properties of correlation functions.- Elementary prediction ?.- 2.7 Input-output relationships.- Convolution.- Nonstationary processes.- Output power in the steady state.- Response of linear systems to white noise.- Response of linear systems to slowly varying input.- Single, double, and triple integration.- 2.8 Spectral analysis.- The self-spectrum.- Parseval's theorem.- Spectral decomposition.- Cross-spectrum.- Problems.- Appendix A2: Integration of power density spectra.- References.- 3. Inertial Force Sensors-Accelerometers.- 3.0 Introduction.- 3.1 Specific force readings on moving platforms.- Elementary strapdown mechanization for vehicle guidance.- 3.2 Leveling the supporting platform.- Mathematical Schuler pendulum.- Physical Schuler pendulum.- 3.3 Schuler frequency on other planets.- 3.4 Force balance accelerometers.- Pickoff considerations.- Spring-mass accelerometer model.- The capacitive detector.- Implementation of loop closure.- The Q-flex accelerometer.- 3.5 Measurement of angular acceleration.- Possible approaches.- Angular accelerometers.- Accelerometer pairs.- Differentiating angular rates.- 3.6 Integrating accelerometers.- 3.7 Vibrating beam accelerometers.- Background.- Principle of operation.- Acceleration-to-frequency conversion.- Double ended tuning fork.- Crystal con
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