MATLAB Signal Generator Simulation

Chapter One Introduction

1.1 Background and research significance of the paper

In the testing and simulation of modern sonar, radar and other communication systems, high-precision arbitrary waveform signals are required. The reconstruction technology of arbitrary waveform signals is also one of the key technologies in application fields such as acoustics and speech signal synthesis. However, due to confidentiality and cost reasons, it is impossible to conduct a large number of field experiments for a long time during the development of sonar, radar and other communication systems. In most cases, it is necessary to reconstruct these random signals with certain characteristics in the laboratory for system testing, system analysis and semi-physical simulation research.

Moreover, with the development of communication technology, there are more and more types of communication signals, and with the development of communication industry, the number of communication networks is also increasing. How to intercept the enemy's communication signals, predict and interfere with them, and thus hinder the enemy's normal communication, is the main research content of communication confrontation. In the study of communication confrontation, in order to simulate real scenes, communication signal generators are also indispensable instruments. However, the communication signal generators on the market are very expensive and have relatively simple functions. Therefore, it is of great theoretical significance and practical value to carry out research on high-precision reconstruction methods of communication signals with arbitrary waveforms.

In the process of generating arbitrary waveform time domain signals, there are two design methods: hardware and software. Matlab simulation is realized through software programming. Matlab is the abbreviation of Matrix Laboratory, which is a commercial mathematical software produced by MathWorks in the United States. MATLAB can perform matrix operations, draw functions and data, implement algorithms, create user interfaces, connect programs in other programming languages, etc. It is mainly used in engineering calculations, control design, signal processing and communication, image processing, signal detection, financial modeling design and analysis, etc. Graphical User Interface (GUI for short) refers to a computer operation user interface displayed in a graphical way. Compared with the command line interface used in early computers, the graphical interface is visually easier for users to accept. Matlab comes with a powerful GUI tool. The emergence of Matlab simulation technology also provides strong technical support for the study of communication signals that generate arbitrary waveforms.

Arbitrary waveform generators can not only generate common waveforms such as sine, cosine, square, triangle and sawtooth waves, but also use various editing methods to generate truly arbitrary waveforms that traditional function generators cannot generate. For example, it can simulate waveforms such as coded radar signals, submarine characteristic signals, disk data signals, mechanical vibration transients, TV signals, and various neural pulses.

1.2 Development and current status of MATLAB simulation technology

1.2.1 Overview of MATLAB

　　MATLAB stands for Matrix Laboratory. In addition to its excellent numerical computing capabilities, it also provides professional-level symbolic computing, word processing, visual modeling and simulation, and real-time control functions.

　　The basic data unit of MATLAB is the matrix. Its command expression is very similar to the forms commonly used in mathematics and engineering. Therefore, it is much simpler to use MATLAB to solve problems than to use C, FORTRAN and other languages ​​to accomplish the same task.

　 The currently popular MATLAB 7.0/Simulink 3.0 includes a main package with hundreds of internal functions and more than thirty toolkits (Toolbox). Toolkits can be divided into functional toolkits and subject toolkits. Functional toolkits are used to expand MATLAB's symbolic computing, visual modeling and simulation, text processing and real-time control functions. Subject toolkits are highly professional toolkits, control toolkits, signal processing toolkits, communication toolkits, etc. all belong to this category.

1.2.2 Historical Background of MATLAB

　 In the mid-1970s, Dr. Cleve Moler and his colleagues developed a FORTRAN subroutine library called EISPACK and LINPACK with funding from the U.S. National Science Foundation. EISPACK is a FORTRAN library for eigenvalue solutions, and LINPACK is a library for solving linear equations. At the time, these two libraries represented the highest level of matrix operations.

　 In the late 1970s, Cleve Moler, the head of the Computer Department at the University of New Mexico, used his spare time to write interface programs for EISPACK and LINPACK for his students. In the following years, MATLAB was used as teaching auxiliary software in many universities and was widely circulated as free software for the general public.

　 In the spring of 1983, Cleve Moler, together with Steve Bangert, developed the second generation of professional version using C language. This generation of MATLAB language has both numerical calculation and data visualization functions.

　 In 1984, Cleve Moler and John Little founded Math Works, officially bringing MATLAB to market and continuing the research and development of MATLAB.

　 Among the more than 30 mathematical science and technology application software today, in terms of the original core of software mathematical processing, they can be divided into two categories. One is numerical calculation software, such as MATLAB, Xmath, Gauss, etc. This type of software is good at numerical calculation and is efficient in processing large amounts of data; the other is mathematical analysis software, such as Mathematica, Maple, etc. This type of software is good at symbolic calculation and can provide analytical solutions and arbitrary precise solutions. Its disadvantage is that it is less efficient when processing large amounts of data. MathWorks has followed the trend of multi-functional needs and, based on its excellent numerical calculation and graphic capabilities, has taken the lead in developing its symbolic calculation, text processing, visual modeling and real-time control capabilities at a professional level, and has developed a new generation of scientific and technological application software MATLAB that is suitable for the requirements of multiple disciplines and departments. After years of international competition, MATLAB has already occupied a dominant position in the numerical software market.

Today, after continuous improvement by MathWorks, MATLAB has developed into a powerful large-scale software suitable for multiple disciplines and multiple work platforms. Abroad, MATLAB has withstood the test of many years. In universities in Europe and the United States, MATLAB has become a basic teaching tool for advanced courses such as linear algebra, automatic control theory, mathematical statistics, digital signal processing, time series analysis, and dynamic system simulation.

1.2.3 Language Features of MATLAB

The reason why a language can be popularized so quickly and show such vigorous vitality is that it has characteristics different from other languages. Just as high-level languages ​​such as FORTRAN and C free people from the need to directly operate computer hardware resources, MATLAB, known as the fourth-generation computer language, uses its rich function resources to free programmers from cumbersome program codes. The most prominent feature of MATLAB is its simplicity. MATLAB replaces the lengthy codes of C and FORTRAN with more intuitive codes that conform to people's thinking habits. MATLAB provides users with the most intuitive and concise program development environment. The following is a brief introduction to the main features of MATLAB.

1) The language is concise and compact, easy to use and flexible, with extremely rich library functions. 2) Rich operators. 3) MATLAB has both structured control statements (such as for loops, while loops, break statements and if statements) and object-oriented programming features. 4) The program restrictions are not strict, and the program design has a large degree of freedom. 5) The program is very portable and can basically run on various models of computers and operating systems without modification. 6) MATLAB has powerful graphics functions. 7) The disadvantage of MATLAB is that it executes programs slower than other high-level programs. 8) Powerful toolboxes. 9) Openness of source programs.

1.3 Development and Current Status of Signal Generators

Before the 1970s, function signal generators could provide several commonly used standard waveforms such as sine waves, cosine waves, square waves, and triangle waves. To generate other waveforms, more complex circuits and electromechanical methods were required. The waveform generators of this period mostly used analog electronic technology, and the circuits composed of analog devices had the disadvantages of large size, high price, and high power consumption. In addition, to generate more complex signal waveforms, the circuit structure was very complex. At the same time, there were two main outstanding problems. One was that the output frequency was adjusted by adjusting the potentiometer, so it was difficult to adjust the frequency to a fixed value; the other was that the duty cycle of the pulse could not be adjusted.

After the 1970s, the emergence of microprocessors allowed the use of processor A/D and D/A, hardware and software to expand the functions of waveform generators and generate more complex waveforms. The waveform generators of this period were mostly software-based, which essentially used microprocessors to program DACs to generate a variety of simple waveforms.

The main implementation methods of signal generation can be divided into analog and digital according to the implementation ideas, and can be divided into four types according to the implementation methods: direct method, phase-locked method, direct digital method and hybrid method.