Introduction of Weak Signal Detection

课程名称 (Course Name) ：微弱信号检测Detection of weak signals

课程代码 (Course Code）：X035504

学分/学时 (Credits/Credit Hours)：2.0 /36

开课时间 (Course Term )：春spring

开课学院（School Providing the Course）: 电子信息与电气工程学院 seiee

任课教师（Teacher）: 杨明 Yang Ming

课程讨论时数（Course Discussion Hours）: 2  小时(Hours)

课程实验数（Lab Hours）:   0 小时(Hours)

课程内容简介(Course Introduction):

Detection of electric signals in nano-volt level and noise-reduction pickup designs are frequent practice in scientific research and engineering. The detection and analyses of seismic signal, the measurement of the intensity of florescence when analyzing special materials, the receiving of the signals transmitted by satellites, the detection of infrared or bio-electrical signal and etc. are all applications of low level signal detection techniques.

The weak signal detection technology is able to improve measurement resolution and accuracy greatly, and it is also a key measure to explore nature phenomenon, uncovering discoveries and developing new technology. Weak signal detection technology is widely used in physics, chemistry, biomedicine, remote sensing technique, material science and etc. By means of the concerned principle and method, many weak signals undetectable with traditional method, like weak florescence, nanometer-displacement, micro-vibration, small change of temperature for instance, can be measured.

Since the noise level sets a limit of lower bound on the magnitude of a signal that can be amplified, the graduate course Detection of Weak Signals will mainly introduce intrinsic noise generation mechanism, the noise models of the most encountered electronic devices，and the general principles of low noise design circuits. The purpose is to reduce the level of intrinsic noises in the electrical circuits, which is necessary to amplify the weak signals. The course also cover some fundamentals of prevailing signal processing theories  such as stochastic resonance techniques to further suppress the noise influences, and pick up weak signals from the noises.

The contents of this course cover three aspects as follows:

1.         Fundamentals of electric noise and low noise electronic design. Mainly introduce the statistic characteristics of random noise, intrinsic noise physical processes, and the noise models of electronic devices.

2.         Typical low level signal detection method and instruments. Mainly introduce low noise preamplifier and its parameters design.

3.        Low level signal detection and processing methods, such as adaptive filter, stochastic resonance techniques, and signal detection in chaos are also covered.

教学大纲(Course Teaching Outline):

1\ Introduction, 1 class hour, introduces references, grading, office hours and contacts, and one example for detection of weak signals, gravitational wave detection.

2\ Fundamental Concepts of Noise, 5 class hours, introduce some basic concepts about the noise, including intrinsic and extrinsic noise, signal theory approach, and probabilistic approach.

3\ Physical Noise Sources, 9 class hours, introduce mechanism and the model of thermal noise, diffusion noise, shot noise, quantum noise, generation – recombination noise, excess noise, burst noise, and avalanche noise.

4\ Noise Models of Electronic Devices, 9 class hours, introduce the estimation of resistor noise, capacitor and inductor and battery noise, junction diode noise, bipolar transistor noise, junction field effect transistor noise, and operational amplifier noise.

5\ Low-noise Circuit Designs, 6 class hours, introduce rules of Low-noise design, noise matching with a coupling transformer, noise matching by paralleling input devices, selection of active devices, sensor and its preamplifier.

6\ Low level signal detection such as lock-in amplifier and signal processing methods such as adaptive filter, stochastic resonance techniques, and signal detection in chaos are selective, and one of them has to be chosen as the topic of the “project” ,  writing a 4000 words, journal format paper.  

课程进度计划(Course Schedule):

Week 1: introduction of course, gravitational wave detection, basic concepts of the noise, including intrinsic and extrinsic noise

Week 2: signal theory approach, and probabilistic approach

Week 3: mechanisms of thermal noise, diffusion noise

Week 4: mechanisms of shot noise, quantum noise, generation – recombination noise

Week 5: mechanisms of excess noise, burst noise, and avalanche noise

Week 6: estimation of resistor noise, capacitor noise, and inductor noise

Week 7: estimation of battery noise, junction diode noise, bipolar transistor noise

Week 8: estimation of junction field effect transistor noise, and operational amplifier noise

Week 9: rules of Low-noise design, the noise reduction by noise matching with a coupling transformer

Week 10: the noise reduction by noise matching by paralleling input devices, selection of active devices, sensor and its preamplifier

Week 11: examination

课程考核要求(Course Assessment Requirements)：

1\Class discussion: 10%, make sure you understand the basic concepts and approaches

2\Homework: 15%

3\Project:15%: 4000 words, journal paper format, describing the principle, simulation, discussion and application of lock-in amplifier, stochastic resonance technique, chaos, adaptive filter, or something interesting for the detection of weak signals.

4\Final Exam: 60%

参考文献(Course References)：

1. Weak Signal Detection, Jinzhan Gao, TsinghuaUniversityPress, Beijing 2004

2. Electronic Noise and Interfering Signals, Principle and Applications, G. Vasilescu, Springer-Verlag Berlin Heidelberg 2005

3. Advanced Theory of Signal Detection – Weak Signal Detection in Generalized Observation, Iickho Song, Jinsoo Bae, Sun Yong Kim, Springer – Verlag Berlin Heidelberg New York 2002

4. Correlation-Based Measurement Systems, J Jordan, P. Bishop, B. Kiani, Ellis Horwood Limited 1989