滤波器原理:滤波器就是对特定的频率或者特定频率以外的频率进行消除的电路,被广泛用于通信系统和信号处理系统中。从功能角度,数字滤波器对输入离散信号的数字代码进行运算处理,以达到滤除频带外信号的目的。
有限冲激响应(FIR)滤波器就是一种常用的数字滤波器,采用对已输入样值的加权和来形成它的输出。其系统函数为:
其中表示延时一个时钟周期,表示延时两个周期。
对于输入序列X[n]的FIR滤波器可用下图所示结构示意图来表示,其中X[n]是输入数据流。各级的输入连接和输出连接称为抽头,系数被称为抽头系数。一个M阶的FIR滤波器将会有M+1个抽头。通过移位寄存器用每个时钟边沿n(时见下标)处的数据流采样值乘以抽头系数,并将它们加起来形成输出。
其verilog HDL设计代码为:
//FIR滤波器设计的verilog HDL程序
module FIR(Data_out, Data_in, clock, reset);
output[9:0] Data_out;
input[3:0] Data_in;
input clock, reset;
wire[9:0] Data_out;
wire[3:0] samples_0,samples_1,samples_2,samples_3,
samples_4,samples_5,samples_6,samples_7,samples_8;
//例化模块
shift_register U1(.Data_in(Data_in), .clock(clock), .reset(reset),
.samples_0(samples_0),.samples_1(samples_1),
.samples_2(samples_2),.samples_3(samples_3),
.samples_4(samples_4),.samples_5(samples_5),
.samples_6(samples_6),.samples_7(samples_7),
.samples_8(samples_8));
caculator U2(.samples_0(samples_0),.samples_1(samples_1),
.samples_2(samples_2),.samples_3(samples_3),
.samples_4(samples_4),.samples_5(samples_5),
.samples_6(samples_6),.samples_7(samples_7),
.samples_8(samples_8), .Data_out(Data_out));
endmodule
//移位寄存器模块
//移位寄存器用于存储输入的数据流,本例中主要负责存储8个4位宽输入数据信号,作为Caculator模块的输入。
module shift_register(Data_in, clock, reset, samples_0, samples_1, samples_2, samples_3,
samples_4, samples_5, samples_6, samples_7, samples_8);
input[3:0] Data_in;
input clock, reset;
output[3:0] samples_0, samples_1, samples_2, samples_3,
samples_4, samples_5, samples_6, samples_7, samples_8;
reg[3:0] samples_0, samples_1, samples_2, samples_3,
samples_4, samples_5, samples_6, samples_7, samples_8;
always@(posedge clock or posedge reset)
begin
if(reset)
begin
samples_0 <= 4'b0;
samples_1 <= 4'b0;
samples_2 <= 4'b0;
samples_3 <= 4'b0;
samples_4 <= 4'b0;
samples_5 <= 4'b0;
samples_6 <= 4'b0;
samples_7 <= 4'b0;
samples_8 <= 4'b0;
end
else
begin
samples_0 <= Data_in;
samples_1 <= samples_0;
samples_2 <= samples_1;
samples_3 <= samples_2;
samples_4 <= samples_3;
samples_5 <= samples_4;
samples_6 <= samples_5;
samples_7 <= samples_6;
samples_8 <= samples_7;
end
end
endmodule
//计算模块
//Caculator模块用于进行8输入信号与抽头系数的乘法和累加,并产生滤波之后输出信号Data_out。应该指出
//的是,FIR滤波器系数具有对称性,在本例中b0 = b8, b1 = b7, b2 = b6, b3 = b5,因此,可以通过先
//将输入信号相加再与抽头系数相乘的方式,减少乘法器电路的数量和芯片面积
module caculator(samples_0, samples_1, samples_2, samples_3,samples_4,
samples_5, samples_6, samples_7, samples_8, Data_out);
input[3:0] samples_0, samples_1, samples_2, samples_3,
samples_4, samples_5, samples_6, samples_7, samples_8;
output[9:0] Data_out;
wire[9:0] Data_out;
wire[3:0] out_tmp_1, out_tmp_2, out_tmp_3, out_tmp_4;
wire[7:0] out1, out2, out3, out4, out5;
parameter b0 = 4'b0010;
parameter b1 = 4'b0011;
parameter b2 = 4'b0110;
parameter b3 = 4'b1010;
parameter b4 = 4'b1100;
wallace U1(.x(b0), .y(out_tmp_1), .out(out1));
mul_addtree U2(.mul_a(b1), .mul_b(out_tmp_2), .mul_out(out2));
mul_addtree U3(.mul_a(b2), .mul_b(out_tmp_3), .mul_out(out3));
mul_addtree U4(.mul_a(b3), .mul_b(out_tmp_4), .mul_out(out4));
mul_addtree U5(.mul_a(b4), .mul_b(samples_4), .mul_out(out5));
assign out_tmp_1 = samples_0 + samples_8;
assign out_tmp_2 = samples_1 + samples_7;
assign out_tmp_3 = samples_2 + samples_6;
assign out_tmp_4 = samples_3 + samples_5;
assign Data_out = out1 + out2 +out3 +out4 +out5;
endmodule
module mul_addtree(mul_a, mul_b, mul_out);
input[3:0] mul_a, mul_b;
output[7:0] mul_out;
wire[7:0] mul_out;
wire[7:0] stored0, stored1, stored2, stored3;
wire[7:0] add01, add23;
assign stored3 = mul_b[3]?{1'b0, mul_a, 3'b0}:8'b0;
assign stored2 = mul_b[2]?{2'b0, mul_a, 2'b0}:8'b0;
assign stored1 = mul_b[1]?{3'b0, mul_a, 1'b0}:8'b0;
assign stored0 = mul_b[0]?{4'b0, mul_a}:8'b0;
assign add01 = stored1 + stored0;
assign add23 = stored3 + stored2;
assign mul_out = add01 +add23;
endmodule
module wallace(x,y,out);
parameter size = 4; //定义参数,乘法器的位数
input [size - 1 : 0] x,y; //输入y是乘数,x是被乘数
output [2*size - 1 : 0] out;
wire [size*size - 1 : 0] a; //a为部分积
wire [1 : 0] b0, b1; //第一级的输出,包含进位
wire [1 : 0] c0, c1, c2, c3; //第二级的输出,包含进位
wire [5 : 0] add_a, add_b; //第三极的输入
wire [6 : 0] add_out; //第三极的输出
wire [2*size - 1 : 0] out; //乘法器的输出(组合逻辑)
assign a = {x[3],x[2],x[3],x[1],x[2],x[3],x[0],x[1],
x[2],x[3],x[0],x[1],x[2],x[0],x[1],x[0]}
&{y[3],y[3],y[2],y[3],y[2],y[1],y[3],y[2]
,y[1],y[0],y[2],y[1],y[0],y[1],y[0],y[0]}; //部分积
hadd U1(.x(a[8]), .y(a[9]), .out(b0)); //2输入半加器(第一级)
hadd U2(.x(a[11]), .y(a[12]), .out(b1));//第一级
hadd U3(.x(a[4]), .y(a[5]), .out(c0)); //第二级
fadd U4(.x(a[6]), .y(a[7]), .z(b0[0]), .out(c1)); //3输入全加器(第二级)
fadd U5(.x(b1[0]), .y(a[10]), .z(b0[1]), .out(c2));
fadd U6(.x(a[13]), .y(a[14]), .z(b1[1]), .out(c3));
assign add_a = {c3[1],c2[1],c1[1],c0[1],c0[0],a[2]}; //加法器(第三极)
assign add_b = {a[15],c3[0],c2[0],c1[0],a[3],a[1]};
assign add_out = add_a + add_b;
assign out = {add_out,a[0]};
endmodule
//全加器模块
module fadd(x, y, z, out);
input x, y, z;
output [1 : 0] out;
assign out = x + y + z;
endmodule
//半加器模块
module hadd(x, y, out);
input x, y;
output [1 : 0] out;
assign out = x + y;
endmodule
测试代码为:
//测试文件
`timescale 1ns/1ns;
module FIR_tb;
reg clock, reset;
reg[3:0] Data_in;
wire[9:0] Data_out;
FIR U1(.Data_out(Data_out), .Data_in(Data_in), .clock(clock), .reset(reset));
initial
begin
Data_in = 0;
clock = 0;
reset = 1;
#10 reset =0;
end
always
begin
#5 clock <= ~clock;
#5 Data_in <= Data_in + 1;
end
endmodule
在Modelsim中仿真所得波形如下:
放大截图为:
下面进行MATLAB生成滤波器的实验:
MATLAB生成30阶低通1MHz海明窗函数设计步骤:
(1)在MATLAB命令窗口中输入“fdatool”出现如下对话框:
(2)设定为低通滤波器。
(3)选择FIR滤波器的设计类型为窗函数。
设置FIR滤波器为30阶滤波器,选择窗函数的类型为海明窗函数,海明窗函数可以得到旁瓣更小的效果,能量更加集中在主瓣中,主瓣的能量约占99.963%,第一旁瓣的峰值比主瓣小40dB,但主瓣宽度与海明窗相同。它定义为:
(4)输入抽样频率和截止频率,分别是16MHz和1MHz。
(5)点击Design Filter 得到结果,如下图:
(6)量化输入输出,点击工作栏左边的量化选项,即“set quantization parameters”选项,选择定点,设置输入字长为8,其他选择默认,如下图示:
设置完成后,点击Targets中Generate HDL,选择生成Verilog 代码,设置路径,MATLAB即可生成设计好的滤波器Verilog HDL 代码以及测试文件,仿真结果如下图:
如上图所示,当输入为线性,或者输入频率较低时,输出幅度不会被抑制,当输入频率较高,输出幅度会受到大幅度抑制,而当输入为白噪声或者混频信号时,滤波器会过滤掉高频信号。