麦克风定位matlab,MATLAB代做|FPGA代做|simulink代做–无线麦克风阵列的定位

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MATLAB程序下载——一基于MATLAB的无线麦克风阵列的定位。

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Part74设备(无线麦克风)检测 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5%%%%%%%%%%%%%%%%%%%%%%%%%%%%

clear all;

close all;

echo on;

connections1=[1 0 1 0 0 ];

connections2=[1 1 1 0 1 ];

gold_seq=PN_1(connections1,connections2);

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% AWGN noise %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%555%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

val=0.5;

%for snr=0:val:20

for snr=0:val:20

col=(snr+val)/val;                           % 数组长度

Ta(col)=0;                           % 加权阈值

Tb(col)=0;                           % 自适应双阈值

Tc(col)=0;                           % 自适应单阈值

Td(col)=0;                           % 固定阈值

% 检测概率

Fa(col)=0;                           % 加权阈值

Fb(col)=0;                           % 自适应双阈值

Fc(col)=0;                           % 自适应单阈值

Fd(col)=0;                           % 固定阈值

% 漏检概率

Ea(col)=0;                           % 加权阈值

Eb(col)=0;                           % 自适应双阈值

Ec(col)=0;                           % 自适应单阈值

Ed(col)=0;                           % 固定阈值

for m=1:1:10

clc% 仿真次数

to=0.2;                                                             % 接收信号的持续时间

[R,r] = wireless_microphone(to);                                    % 待感知信号

signal_power = 6225.6;                                              % 信号功率

SIGMA=sqrt(6225.6/10^(0.1*snr));

noise = zeros(1,2048);

MU = zeros(1,2048);

noise = normrnd(MU,SIGMA);                                          % 产生AWGN

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%  transmitted signal   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% 假设主用户随机占用信道

for j=1:1:8                                                        % 改变伪随机序列长度，随机改变主用户的占用情况

for k=1:1:8

if (gold_seq(j,k)==1)

xx(1,(length(r)*(k-1)+1):length(r)*k)=r;         % 伪随机码为1，主用户占用信道；

else

xx(1,(length(r)*(k-1)+1):length(r)*k)=r;           % 伪随机码为0，主用户未占用信道；只有存在噪声

end

end

end

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Muti-cycles detection %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

nn=noise(1,1:2048);

rr=r(1,1:2048);

S=40;                                                             % 循环周期数S，可改为 20,40,50

[l_noise,threshold]=estimate(nn,S);

l_noise=abs(l_noise);                                             % 噪声估计值

[l_signal,threshold]=estimate(rr,S);

l_signal=abs(l_signal);                                           % 信号估计值

for ii=1:8

rr(1,1:2048)= xx(1,(2048*(ii-1)+1):2048*ii);              % 每 0.2s 就感知一次信道，进行多周期循环检测

[ll_signal,threshold]=estimate(rr,S);

ll(ii,m)=abs(ll_signal);

end

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%     计算自适应阈值    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%      `

Pfa=0.3;                                                      % 虚警概率可改：0.05,0.1,0.2,0.3

aa=sqrt(2*log10(1./Pfa));

th=l_noise*aa;

adap_thres(m)=th;

%m=m+1;

end

th2=mean(l_noise(1,:));

th3=mean(ll_signal(1,:));

snr_avg=(th3.^2)/(th2.^2);

FT=0.3;                                               % 指数加权因子FT可改为 0.1,0.3,0.9,1.2

th4=threshold*(sqrt(snr_avg)/th3).^FT;

K=0.2;                                                % 乘性因子K可改为 0.01,0.03,0.1,0.2

th6(1,:)=K*l_noise(1,:)/aa;

ouyany=5

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%  判决   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

[FA,EA,TA]=decisionv(ll,th4,gold_seq);                % 加权阈值的判决

[FB,EB,TB]=decisionv(ll,th6,gold_seq);            % 自适应双阈值的判决

[FC,EC,TC]=decisionv(ll,adap_thres,gold_seq);     % 自适应单阈值的判决

[FD,ED,TD]=decisionv(ll,threshold,gold_seq);      % 固定阈值的判决

ouyany=4

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 统计判决结果   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% 虚警概率

Ta(col)=TA/20*8;   % 加权阈值

Tb(col)=TB/20*8;   % 自适应双阈值

Tc(col)=TC/20*8;   % 自适应单阈值

Td(col)=TD/20*8;   % 固定阈值

% 检测概率

Fa(col)=FA/20*8;   % 加权阈值

Fb(col)=FB/20*8;   % 自适应双阈值

Fc(col)=FC/20*8;   % 自适应单阈值

Fd(col)=FD/20*8;   % 固定阈值

% 漏检概率

Ea(col)=EA/20*8;  % 加权阈值

Eb(col)=EB/20*8;  % 自适应双阈值

Ec(col)=EC/20*8;  % 自适应单阈值

Ed(col)=ED/20*8;  % 固定阈值

end

[Fa1]=averge(Fa);

[Fb1]=averge(Fb);

[Fc1]=averge(Fc);

[Fd1]=averge(Fd);

[Ea1]=averge(Ea);

[Eb1]=averge(Eb);

[Ec1]=averge(Ec);

[Ed1]=averge(Ed);

[Ta1]=averge(Ta);

[Tb1]=averge(Tb);

[Tc1]=averge(Tc);

[Td1]=averge(Td);

Fa1=sort(Fa1);

Fb1=sort(Fb1);

Fc1=sort(Fc1);

Fd1=sort(Fd1);

Ta1=sort(Ta1);

Tb1=sort(Tb1);

Tc1=sort(Tc1);

Td1=sort(Td1);

Ea1=sort(Ea1);

Eb1=sort(Eb1);

Ec1=sort(Ec1);

Ed1=sort(Ed1);

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

Ed_maximum=max(Ed(:));

for n=1:2:41

tao=log(1-Td(n))/log(Ed(n));

Ni(n)=log((1-Fd(n))/Fd(n))*(tao/((((Ed_maximum*((1-Fd(n))^(-1))-1)^(-1))*(tao))-tao));   % 每种SNR下需要实际频谱感知的次数

Nj(n)=round(abs(Ni(n)));

end

figure;

plot(Nj,’r-*’);

xlabel(‘SNR’);

ylabel(‘感知次数’);

title(‘感知次数’);

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%  plot detection picture %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

figure

snr=0:1:20;

k=1:2:41;

plot(snr,Fa1(k),’-ro’,snr,Fb1(k),’–k*’,snr,Fc1(k),’-cd’,snr,Fd1(k),’b+-‘)

legend(‘(1)自适应加权阈值’,'(2)自适应双门限阈值’,'(3)自适应单门限阈值’,'(4)固定阈值’)

grid on ;

xlabel(‘SNR/db’)

ylabel(‘Pd’)

title(‘无线麦克风信号正确检测概率图’);

figure

subplot(2,1,1)

plot(xx);

xlabel(‘时间[s]’);

ylabel(‘幅度[V]’);

title(‘间隙发送无线麦克风信号’);

subplot(2,1,2)

bar(ll);

xlabel(‘时间[s]’);

ylabel(‘检测估计值’);

title(‘检测估计值图’);

figure

snr=0:1:20;

k=1:2:41;

plot(snr,Ta1(k),’-ro’,snr,Tb1(k),’–k*’,snr,Tc1(k),’-cd’,snr,Td1(k),’b+-‘)

legend(‘(1)自适应加权阈值’,'(2)自适应双门限阈值’,'(3)自适应单门限阈值’,'(4)固定阈值’)

grid on ;

xlabel(‘SNR/db’)

ylabel(‘Pf’)

title(‘无线麦克风信号虚警概率图’);

figure

snr=0:1:20;

k=1:2:41;

plot(snr,Ea1(k),’-ro’,snr,Eb1(k),’–k*’,snr,Ec1(k),’-cd’,snr,Ed1(k),’b+-‘)

legend(‘(1)自适应加权阈值’,'(2)自适应双门限阈值’,'(3)自适应单门限阈值’,'(4)固定阈值’)

grid on ;

xlabel(‘SNR/db’)

ylabel(‘Pm’)

title(‘无线麦克风信号漏检概率图’);

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