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An Introduction to Signal Processing

Signal processing is an emerging technology that incorporates the fundamental theory, algorithms, processing, and transferring information in different patterns, which is broadly designated as signals. Transmission of information, or signals, is done through a channel. The digital signal processor consists of anti-aliasing filter and analog to digital and digital to analog converters. Analog, frequency, and digital modulations are various aspects of transmission. The concept of signal processing is a part of the FE exam syllabus, and it is reviewed in most FE exam prep courses. The main goal of signal processing applications is to be efficient and perform reliable transmission, display of information, and storage.

Digital Signal Processing Applications

Audio compression, digital image processing, compression of videos, speech processing and recognition, digital communications, radio detection and ranging systems, seismology, and sound navigation and ranging systems are examples of digital signal processing applications. The implementation of digital signal processing is based on the requirements of the application.

Digital Signal Processing Applications - Engineering Devices

Radar is an object-detection system; it uses radio waves to control the range, angle, or velocity of objects. Radar is used to transmit radio signals at distant objects and analyze the reflection. Radar is used for air-traffic control to avoid mid-air collision and to predict weather conditions. Radar is also used in meteorology to aid in forecasting the weather.

Sonar is an application of digital signal processing (DSP); sonar uses sound propagation to navigate and communicate with or detect an object under the surface of the water. Generally, two types of technologies are used in sonar: passive sonar and active sonar technologies. Passive sonar is used to listen to the sound of the vessels; active sonar is used to release pulses of sounds and to listen to echoes. Sonar may also be used for acoustic measurements.

The Components of Digital Signal Processing

Computation: performs mathematical operations and processes by accessing the program from the program memory and the information stored in the data memory.

Data Memory: stores the information to be processed and works with program memory.

Program Memory: stores the programs; the processor uses the program memory to compress or manipulate data.

Input/Output Ports: used for data processing and analysis.

Digital Signal Processor Performance

The most important challenge in executing DSP algorithms is transferring the data from the memory. The goal of digital signal processing is to measure, filter, and compress analog signals. General-purpose microprocessors can execute digital signal processing algorithms successfully. DSPs use a special memory architecture that can fetch multiple data and instructions at a time. DSP processors execute one instruction per clock cycle in complex or multi-operation type of instructions. These processors include a single multiplier or MAC unit and ALU unit. DSP processors show good performance even at the modest power and memory usage. Digital signal processing is one of the courses taught in undergraduate electrical engineering, and it is reviewed in fundamentals of engineering exam prep courses for those taking the FE exam.