What is Analog Signal Processing?

Analog signal processing A generic term for processing methods such as signal processing and transformation using analog methods.

Analog signal processing A generic term for processing methods such as signal processing and transformation using analog methods.

Chinese name

Analog signal processing

Foreign name

analog signal processing

Applied discipline

Communication

Features

Analog, signal processing

Definition of analog signal processing

Generally, the signals encountered in nature are analog signals, which are continuous in the amplitude and time domains. Amplifying, filtering, modulating, demodulating, and various frequency conversions of these signals are all analog signal processing. Analog signal processing is relative to digital signal processing. Digital signal processing uses digital computer methods to process signals. In order to achieve digital processing, the signal must first be sampled in time, quantized in amplitude, and then input to a computer for processing. After the processing is finished, the digital signal is filtered again and restored to an analog signal. The advantages of analog signal processing are good real-time performance, and the components and equipment used are small and inexpensive. However, because of its limitations in terms of accuracy, stability, and integration of the device, it is even more difficult to perform program-controlled multiplexing. Therefore, many complex signal processing operations are difficult to complete by analog methods, and need to be performed by digital signal processing methods.

Nevertheless, analog signal processing still has considerable potential in research and applications.

Analog signal processing

An analog signal is a signal whose information parameters appear as continuous within a given range. Or, in a continuous time interval, the characteristic quantity representing the information can be presented as a signal of any value at any instant.

Analog signals are mainly continuous signals as opposed to discrete digital signals. Analog signals are distributed in various corners of the natural world, such as changes in air temperature, while digital signals are artificially abstracted and discontinuous in amplitude. Electrical analog signals mainly refer to electrical signals with continuous amplitude and phase. This signal can be used by analog circuits for various operations, such as amplification, addition, and multiplication.

Analog signals refer to information expressed by continuously changing physical quantities. The amplitude, frequency, or phase of a signal changes continuously over time. The sound signal of broadcasting, the image signal of television, etc.

The main advantage of analog signals is their precise resolution, which ideally has infinite resolution. Compared to digital signals, analog signals have a higher information density. Since there is no quantization error, it can describe the true value of physical quantities in nature as close as possible.

Another advantage of analog signals is that when the same effect is achieved, analog signal processing is simpler than digital signal processing. The processing of analog signals can be directly implemented by analog circuit components (such as operational amplifiers, etc.), while digital signal processing often involves complex algorithms, and even requires a special digital signal processor.

The main disadvantage of an analog signal is that it is always affected by noise (undesirably random values in the signal). The effects of these random noises can become significant after the signal is duplicated multiple times or transmitted over long distances. In electricity, these negative effects can be alleviated to some extent by using a grounded shield (shield), good line contact, and the use of coaxial cables or twisted pairs.

Noise effects can be detrimental to the signal. Lost analog signals are almost impossible to be restored again, because the amplification of the desired signal will simultaneously amplify the noise signal. If the difference between the noise frequency and the frequency of the desired signal is large, you can filter out noise at a specific frequency by introducing an electronic filter, but this solution can only reduce the impact of noise as much as possible. Therefore, under the action of noise, although the analog signal theoretically has infinite resolution, it is not necessarily more accurate than the digital signal.

Although digital signal processing algorithms are relatively complex, existing digital signal processors can quickly accomplish this task. In addition, the gradual popularization of computers and other systems has made the propagation and processing of digital signals more convenient. Devices such as cameras are gradually becoming digitized, although they must initially receive real physical information in the form of analog signals, and eventually they are converted to digital signals by analog-to-digital converters for easy processing by computers or transmission via the Internet.

Analog signal processing concepts

The conversion and processing of analog signals is a process of directly analyzing and processing continuous-time signals, and it is realized by using an arithmetic network composed of certain mathematical models. Broadly speaking, it includes modulation, filtering, amplification, calculus, power, square root, and division operations. The purpose of analog signal analysis is to facilitate the transmission and processing of signals, such as amplification and long-distance transmission after signal modulation; use of signal filtering to remove noise and frequency analysis; operation evaluation of signals to obtain characteristic parameters, etc.

Although digital signal analysis technology has achieved great development, analog signal analysis is still indispensable. Even in digital signal analysis systems, analog analysis equipment is also required. For example, anti-mixing filtering before digital analysis of continuous time signals, display records after signal processing, etc.
Most of the electrical signals output by sensors cannot be directly transmitted to display, recording or analysis instruments. The main reason is that most of the sensors' electrical signals are weak and need to be further amplified, and some need impedance conversion; some sensors output electrical parameters that need to be converted into electrical energy; the output signal is mixed with interference noise and requires Remove the noise and improve the signal-to-noise ratio; if the test work is only interested in the signals of some frequency bands, it is necessary to separate the required frequency components from the output signal; when digital instruments, meters and computers are used, the analog output signal is still To convert to digital signals and so on. Therefore, the output signal of the sensor must be properly conditioned to make it suitable for subsequent testing. Common signal conditioning links are: bridges, amplifiers, filters, modulators and demodulators.

Analog signal processing flow

Generally speaking, analog signal processing will include processes such as amplification, filtering, modulation, and demodulation, which will affect the effect of signal processing.

Figure 1 Flow chart of analog signal processing