The Effects of Automatic Gain Control Performance on the Tracking Accuracy of Monopulse Radar Systems

This paper analyzes and discusses the capability of human being detection using impulse ultra-wideband (UWB) radar with an improved detection algorithm. The multiple automatic gain control (AGC) technique is employed to enhance the amplitudes of human respiratory signals. Two filters with seven values averaged are used to further improve the signal-to-noise ratio (SNR) of the human respiratory signals. The maximum slope and standard deviation are used for analyzing the characteristics of the received pulses, which can provide two distance estimates for human being detection. Most importantly, based on the two distance estimates, we can accurately judge whether there are human beings in the detection environments or not. The data size can be reduced based on the defined interested region, which can improve the operation efficiency of the radar system for human being detection. The developed algorithm provides excellent performance regarding human being detection, which is validated through comparison with several well-known algorithms.

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Communication system improvement with control performance based on link quality in wireless sensor actuator networks

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v11i6.pp5089-5098 ◽

2021 ◽

Vol 11 (6) ◽

pp. 5089

Author(s):

Nada N. Tawfeeq ◽

Sawsan D. Mahmood

Keyword(s):

Fuzzy Inference ◽

Automatic Gain Control ◽

Gain Control ◽

Adaptive Controller ◽

Link Quality ◽

Wireless Sensor ◽

Control Performance ◽

Validation Data ◽

Inference System ◽

Sensor Actuator

<span lang="EN-US">New communication and networking paradigms started with wireless sensor actuator networks (WSANs) to introduce new applications. One of these is the automatic gain control system (AGC). It will enable a high degree of the decentralized and mobile control. In this study, neural networks (NN) with fuzzy logic (one of the techniques of artificial intelligence (AI)) is used to enhance the control performance depending on the link quality. The NN and fuzzy inference system (FIS) with Mamdani’s method used to build a model reference, adaptive controller, for recompensing for delay time packets losses, and improving the reliability of WSAN. Between 88.62% and 99.99%, validation data is obtained for the medium and high conditions of operation with the proposed algorithm. Experimental and simulation results show a promising approach.</span>

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Research on Measurement Method of Ultrasonic Transit Time based on Automatic Gain Control

2020 39th Chinese Control Conference (CCC) ◽

10.23919/ccc50068.2020.9188416 ◽

2020 ◽

Author(s):

Qinyong Ma ◽

Yuanzheng Zhang

Keyword(s):

Transit Time ◽

Measurement Method ◽

Automatic Gain Control ◽

Gain Control

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Measuring Current in a Power Converter Using Fuzzy Automatic Gain Control

Applied Sciences ◽

10.3390/app11135793 ◽

2021 ◽

Vol 11 (13) ◽

pp. 5793

Author(s):

Bartosz Dominikowski

Keyword(s):

High Resolution ◽

Fuzzy Controller ◽

Automatic Gain Control ◽

Gain Control ◽

Measurement Range ◽

Power Converter ◽

Current Measurement ◽

Dc Power ◽

Programmable Gain ◽

Electric Loads

The accuracy of current measurements can be increased by appropriate amplification of the signal to within the measurement range. Accurate current measurement is important for energy monitoring and in power converter control systems. Resistance and inductive current transducers are used to measure the major current in AC/DC power converters. The output value of the current transducer depends on the load motor, and changes across the whole measurement range. Modern current measurement circuits are equipped with operational amplifiers with constant or programmable gain. These circuits are not able to measure small input currents with high resolution. This article proposes a precise loop gain system that can be implemented with various algorithms. Computer analysis of various automatic gain control (AGC) systems proved the effectiveness of the Mamdani controller, which was implemented in an MCU (microprocessor). The proposed fuzzy controller continuously determines the value of the conversion factor. The system also enables high resolution measurements of the current emitted from small electric loads (≥1 A) when the electric motor is stationary.

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