This paper first introduces the related concepts of FIR digital filter, and uses the FDA TOOL toolbox and Simulink tool in MATLAB to design the FIR bandpass digital filter. The design scheme of FIR digital filter based on Matlab is given. Finally, through modeling and simulation, it is proved that the filter designed in this scheme can quickly and effectively form a conventional digital filter, and realize the FIR filter with different cutoff frequency, which greatly reduces the workload and has strong practicability.
0 Preface
With the development of digitization, intelligence and networking in the information age, digital signal processing has become an extremely important subject and research hotspot, and digital filtering technology has received increasing attention as an important part of the field.
Compared with the IIR digital filter, the FIR filter has been further developed with its great linear phase advantage. The digital filter can be implemented in either hardware or software. The advantage of the latter is that the overall performance can be adjusted by changing the filter parameters. The signal processing toolbox provided by MATLAB has powerful function functions, which can be used not only. Designing digital filters can also make designs the most worrying, so it has become a powerful tool for FIR digital filter design.
1.FIR digital filter
1.1 FIR filter system function
The FIR digital filter is a non-recursive system whose impulse response h(n) is a finite-length sequence whose general form of system function is:
In the above formula, h(n) is a causal sequence, H(z) is an N-1 degree polynomial of z1, and there are only N-1 order poles at Z=0, and there are no poles elsewhere, there are N-1 The zero point is anywhere in the finite Z plane. The basic structure of the FIR system has direct type and cascade type, and has been widely used as a correlator and a canceller in radar signal processing.
1.2 FIR filter design process
The design process of the digital filter is:
1) Determine the performance requirements of the filter according to actual needs. Usually (but not always) is the performance requirement of a given digital filter in the frequency domain, typically amplitude and phase response, ie technical specifications.
2) Find a discrete-time linear system that satisfies the predetermined performance requirements by using a causal-stabilized system function to approximate a given performance requirement to determine the filter coefficients.
3) Implement the designed system with finite precision operations.
This includes selecting the arithmetic structure to quantize the filter coefficients, input variables, intermediate variables, and output variables to a fixed word length.
4) Through simulation, analyze its frequency characteristics and phase characteristics to verify whether the designed system meets the specified performance requirements.
2. Introduction to MATLAB related tools
2.1 FDATOOL Toolbox
FDATOOL is a special toolbox for providing filter design in Matlab software. It can design almost all conventional filters. The interface is divided into two parts, as shown in Figure 1.
The upper part of the interface is the characteristic area, which is used to display various characteristics of the filter.
The lower part of the interface is Design Filter, which is used to set the filter design parameters, mainly divided into: ResoponseType (Filter Type) option, Design Method (Design Method) option, Filter Order (Filter Order) option, Frenquency SpecificaTIons ( Frequency characteristics) options and Magnitude SpecificaTIons options.
2.2 Introduction to Simulink
Simulink is an integrated software package for dynamic system modeling, simulation and comprehensive analysis. It can handle linear and nonlinear systems; discrete systems, continuous systems and hybrid systems; single-task, multi-task discrete event systems, etc. , control, signal processing, power systems and many other fields. The good combination of Simulink and Matlab allows users to use Matlab's rich resources to build simulation models, monitor the simulation process, and modify parameters online and observe the changed results.
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