WO2013097409A1 - 一种基于增强型频谱相关函数的无线信号检测方法 - Google Patents
一种基于增强型频谱相关函数的无线信号检测方法 Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/0006—Assessment of spectral gaps suitable for allocating digitally modulated signals, e.g. for carrier allocation in cognitive radio
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- H—ELECTRICITY
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- H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
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- the invention belongs to the field of cognitive radio technology, and is specifically applied to detecting low-power wireless microphone signals in the perception of blank digital television bands. Background technique
- the invention provides a wireless microphone signal detection method based on an enhanced spectrum correlation function, which is used for solving the problem that the existing wireless microphone signal detection method cannot distinguish between narrowband interference and wireless microphone signal, resulting in extremely high virtual The problem of the police rate and the small number of available blank TV bands.
- a wireless microphone signal detection method based on an enhanced spectral correlation function includes two major steps: Step 1: Obtain a digital signal of a frequency to be detected
- the signal received by the antenna module is sent to the low noise amplifier, and the amplified signal passes through the band pass filter.
- the bandwidth can be adjusted according to actual needs, and then the filtered signal is sent to the orthogonal down converter to select the TV frequency band.
- the internal frequency is used as the local oscillator frequency to perform the lower orthogonal frequency conversion processing on the signal, and then the IQ two-way signal is obtained, and then the two signals are respectively sent through a certain bandwidth low-pass filtering and gain controller, and the IQ two-way signal is sent out.
- Step 2 Enhanced SCF completion detecting wireless microphone signals [ "] of SCF and SCF conjugate of the digital signal x is obtained according to the collected digital signal x ["] Enhanced SCF (/ ). , the following formula can be used:
- M is a positive odd number and M ⁇ N, which is a discrete time Fourier transform of ⁇ [ ⁇ ] and
- test statistics ⁇ x[n]e ⁇
- ⁇ is the value range of the frequency in l ⁇ AJ
- ⁇ is the range of the "cycle frequency in i ⁇ oj”
- the decision threshold of the specific false alarm rate is simulated by a predetermined method, if ⁇ ⁇ ⁇ ⁇ , then For narrowband interference, otherwise it is a wireless microphone signal.
- the present invention proposes a conjugate spectral correlation function and combines spectral correlation functions to form an enhanced spectral correlation function, thereby establishing a wireless microphone signal sensing method based on an enhanced spectral correlation function.
- the method can effectively distinguish between narrowband interference and wireless microphone signals, greatly reducing the false alarm rate caused by narrowband interference, and has the advantage of low complexity.
- FIG. 1 is a schematic flowchart diagram of a method for detecting a wireless microphone signal based on an enhanced spectrum correlation function according to an embodiment of the present invention
- FIG. 6 is a block diagram of a wireless microphone signal sensing process in Embodiment 2 of the present invention.
- Figure 7 is a three-dimensional view of the amplitude of the enhanced spectral correlation function calculated by the equation (6) of the wireless microphone signal obtained according to the experimental procedure described in Figure 6 in Embodiment 2 of the present invention;
- Figure 8 is a three-dimensional view of the amplitude of the enhanced spectral correlation function calculated by the equation (6) according to the narrow-band interference obtained in the experimental flow described in Figure 6 in Embodiment 2 of the present invention.
- the specific embodiment provides a wireless microphone signal detection method based on an enhanced spectrum correlation function. As shown in FIG. 1, the method includes:
- Step 1 receiving an air signal through the antenna module
- Step 2 performing low noise amplification on the received signal
- Step 3 performing band pass filtering on the amplified signal
- Step 4 The filtered signal may be orthogonally down-converted to an intermediate frequency or a baseband according to requirements; Step 5, performing low-pass filtering on the IQ two-way signals from the orthogonal down-converter;
- Step 6 the signal from the low-pass filter is sent to the gain controller for gain adjustment;
- Step 7 the gain-adjusted signal is sent to the analog-to-digital converter for analog-to-digital conversion;
- Step 8 the modulus is The converted digital signal is sent to the time domain signal processing module, where the processing of receiving, downsampling, downconverting, IQ merging, and storing of the signal is completed, and then the M segments required for detection are not overlapped or partially overlapped. Time domain digital signal;
- Step 9 Scan the time domain digital signal to obtain a frequency to be detected.
- Step 10 Calculate a spectrum correlation function of the digital signal to be detected according to formula (2); Step 11, calculating a conjugate spectral correlation function of the digital signal to be detected according to formula (3); Step 12, obtaining an enhanced spectral correlation function of the digital signal of the frequency to be detected according to formula (1); Step 13, using decision theory , for example, obtaining a decision statistic 7 according to equation (4);
- Step 14 Obtain a threshold value Y by a predetermined method simulation or calculation
- Step 15 the comparison result with ⁇ gives a decision, that is, if 7; ⁇ ⁇ , it is narrowband interference, otherwise it is a wireless microphone signal.
- the specific implementation manner proposes a conjugate spectral correlation function, and combines the spectral correlation function to form an enhanced spectral correlation function, thereby establishing a wireless microphone signal sensing method based on the enhanced spectral correlation function, and using the enhanced spectral correlation function.
- the feature is to correctly distinguish between sinusoidal continuous wave (analog narrowband interference) and wireless microphone signal, so as to accurately determine whether the current channel has a wireless microphone signal, which lays a foundation for the effective and full utilization of the TV white space.
- the signal received by the antenna module 101 is sent to a low noise amplifier (LNA) 102, and the amplified signal passes through a band pass filter (BPF) 103.
- LNA low noise amplifier
- BPF band pass filter
- the bandwidth can be adjusted according to actual needs, and then the filtered signal is sent to the orthogonal
- the down converter 105 performs the lower orthogonal frequency conversion processing on the signal of the local oscillator 104 frequency with the frequency point in the selected television frequency band, thereby obtaining the IQ two-way signal, and then letting the two signals pass the low-pass filtering of a certain bandwidth (LPF).
- LPF band pass filter
- ⁇ is the range of frequencies in l ⁇ AJ
- ⁇ is the range of the "cycle frequency in i ⁇ oj". This method does not calculate the amplitude of the SCF over the entire plane, but through a set of finite frequencies. The magnitude of the enhanced spectral correlation function is used to calculate the statistic, thereby reducing computational complexity.
- This embodiment illustrates a system simulation of a wireless microphone detection method based on an enhanced spectrum correlation function. Really.
- the simulation is based on the MATLAB environment.
- the specific simulation steps are as follows:
- the threshold value calculation method is as follows: the Monte Carlo method is used to obtain the statistical distribution characteristics of the test statistic of the sinusoidal continuous wave signal under different SNR, and then the threshold is obtained under a given false alarm rate.
- Figures 2 and 3 depict three-dimensional plots of enhanced spectral correlation functions for wireless microphone signals and sinusoidal continuous wave signals, respectively. The difference between the two can be seen visually.
- Figures 4 and 5 illustrate the performance of detecting wireless microphone signals using enhanced spectral correlation functions under different parameters. It can be seen that when the signal-to-noise ratio is higher than -23dB, the false alarm rate is extremely low for wireless microphone signals greater than 2.
- This embodiment illustrates an actual system implementation based on a periodic diagram wireless microphone detection method.
- the actual system architecture 1 is as shown in FIG. 6:
- the signal received by the antenna module 101 is sent to a low noise amplifier (LNA) 102, and the amplified signal passes through a band pass filter (BPF) 103, and the bandwidth can be adjusted according to actual needs.
- the filtered signal is sent to the orthogonal downconverter 105, and the frequency in the selected TV frequency band is used as the local frequency of the local oscillator 104 to perform orthogonal down-conversion processing on the signal, thereby obtaining two signals of IQ, and then two signals are obtained.
- LNA low noise amplifier
- BPF band pass filter
- the low-pass filter (LPF) 106 and the intermediate frequency amplifier (IF Amp) 107 of a certain bandwidth are respectively sent to the analog-to-digital converter (ADC) 109, and the two channels of the ADC 109 are finally sent out.
- the digital signal is sent to the FPGA 110, and the processing of receiving, downsampling, down-converting, IQ merging, and storing of the signal is completed in the FPGA 110, and then we obtain the time-domain digital signal required for the detection, and the data is sent through the interface such as USB.
- the frequency domain microphone detection algorithm is run in the PC 111, and finally, the current TV band status is judged according to the judgment result.
- the FPGA is controlled by the feedback loop of the local oscillator and the ADC.
- the system architecture 2 as shown in FIG. 7 can also be used.
- the architecture replaces the PC111 module in the architecture 1 with a module with the core of the DSP 113, and the module sends the data from the FPGA 110 through a corresponding interface such as an EMIF port.
- the DSP 113 reads the data from the memory 114 in real time to complete the frequency domain microphone detection algorithm and gives the decision result.
- the decision result can be sent to the peripheral device 112 connected to the DSP, or through some interfaces such as USB.
- the port 115, the network port 116, and the like are transmitted to other devices.
- the obtained data is processed by a frequency domain microphone detection algorithm in the PC.
- the obtained data is processed by a frequency domain microphone detection algorithm in the DSP chip.
- Figure 8 and Figure 9 respectively show the three-dimensional map of the amplitude of the enhanced spectrum correlation function of the measured wireless microphone signal and narrowband interference in the above process.
- the experimental results are basically consistent with the system simulation results.
- the technical solution provided by this embodiment is based on the wireless microphone signal sensing method of the enhanced spectrum correlation function, which can effectively distinguish between narrowband interference and wireless microphone signals, thereby solving the problem that the narrowband interference cannot be distinguished from the wireless microphone signal, so that the current blank
- the major problems in TV band detection have been solved, and the detection method has low algorithm complexity and is easy to implement in practical systems.
- the embodiment further provides a wireless signal detecting device based on an enhanced spectral correlation function, including an antenna module, a low noise amplifier, a band pass filter, a down conversion to an intermediate frequency or a baseband, a low pass filter, and an analog to digital converter.
- an enhanced spectral correlation function including an antenna module, a low noise amplifier, a band pass filter, a down conversion to an intermediate frequency or a baseband, a low pass filter, and an analog to digital converter.
- the signal output end of the antenna module is connected to the signal input end of the low noise amplifier, and the signal output end of the low noise amplifier and the signal input end of the band pass filter Connected, the signal output of the bandpass filter is connected to the signal input of the downconverter to the intermediate frequency or baseband, and the signal output of the downconverter to the intermediate frequency or baseband is shortly connected to the signal input of the low pass filter, and the signal of the low pass filter
- the output end is connected to the signal input end of the analog-to-digital controller, and the signal output end of the analog-digital controller is connected to the signal input end of the time domain signal pre-processing module.
- the antenna module is a receiving antenna of a VHF and UHF band
- the downconverting to an intermediate frequency or a baseband includes setting a frequency of the local oscillator according to a TV frequency band to be detected, and outputting the signal by using a quadrature down converter. Frequency conversion to intermediate frequency or baseband.
- the bandwidth of the low-pass filter needs to be greater than or equal to half of a bandwidth of a television band
- the gain controller includes manually or automatically adjusting an output voltage value or current according to a voltage or current required by the analog-to-digital converter.
- the time domain signal pre-processing module is used to implement two major functions through a programmable chip: one is processing of receiving, downsampling, down-converting, merging, and storing two signals of IQ; the second is for other modules such as this Vibration, analog to digital converters, USB chips, etc. provide the required control signals.
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Abstract
本发明提供了一种基于增强型频谱相关函数的无线麦克风信号检测方法，包括根据采集的数字信号的频谱相关函数以及本发明提出的共轭频谱相关函数获得所述数字信号的增强型频谱相关函数；计算检验统计量并与预定方法模拟或计算得到的判决门限进行比较来判别是否为无线麦克风信号。本发明基于提出的增强型频谱相关函数，解决了现有检测方法中无法将窄带干扰与无线麦克风信号进行区分的问题，使得当前空白电视频段检测中的重大困难得到了解决，同时本检测方法具有低算法复杂度，在实际系统中易于实现。
Description
一种基于增强型频谱相关函数的无线信号检测方法 技术领域
本发明属于认知无线电技术领域， 具体运用于空白数字电视频段感知中对 低功耗无线麦克风信号的检测。 背景技术
美国联邦通信委员会规定电视空白频段感知设备要能检测出信号强度为
-107dbm的无线麦克风信号。 在如此低的信号强度下， 由于杂散辐射、 泄露、 交 调等引起的连续波窄带干扰与麦克风信号很相似，现有的检测方法没有将窄带干 扰与无线麦克风信号进行区分而导致了极高的虚警率，这使得可用空白电视频段 的数目急剧下降。 发明内容
本发明提供了一种基于增强型频谱相关函数的无线麦克风信号检测方法， 用于 解决现有的无线麦克风信号检测方法中存在的无法将窄带干扰与无线麦克风信号 进行区分而导致了极高的虚警率以及可用空白电视频段的数目较少的问题。
本发明的目的是通过以下技术方案实现的：
一种基于增强型频谱相关函数的无线麦克风信号检测方法， 包括两大步骤： 步骤 1 : 获得待检测频点的数字信号
将天线模块接收到的信号送到低噪声放大器中， 放大信号经过带通滤波器， 其 带宽可以根据实际需要进行调整， 接着将滤波后的信号送入正交下变频器， 以所选 电视频段内的频点作为本振频率对信号进行下正交变频处理， 进而得到 IQ两路信 号， 然后让两路信号分别通过一定带宽的低通滤波和增益控制器， 将出来的 IQ两 路信号送入到模数转换器中， 最后将模数转换器出来的两路数字信号送入时域信号 预处理模块中， 在该模块中完成对信号的接收、 下采样、 下变频、 IQ合并以及存储 等处理， 并扫描频域信号从而获得待检测的频点， 进而获得了待检测频点的数字信 号。
步骤 2 : 利用增强型频谱相关函数完成对无线麦克风信号的检测 根据采集的数字信号 x["]的频谱相关函数 以及共轭频谱相关函数 获得所述数字信号 x["]的增强型频谱相关函数 (/)。， 可采用如下的计算公式：
上述的 M是一个正的奇数且 M≤N， 为 χ[·]的离散时间傅里叶变换且
Ν-\
X(f) =∑x[n]e~ 采用适当的检验统计量进行判决， 例如如下的检验统计:
其中， Ψ是 l ^ AJ中频率 的取值范围， Ω是 i ^o j中循环频率"的 取值范围， 通过预定方法模拟得到特定误警率下的判决门限 ^， 若 Τα≤γ， 则为 窄带干扰， 否则为无线麦克风信号。
本发明的有益效果： 本发明提出共轭频谱相关函数， 并结合频谱相关函数形 成增强型频谱相关函数，从而建立基于增强型频谱相关函数的无线麦克风信号感 知方法。所述方法能有效区分窄带干扰和无线麦克风信号， 极大的降低了由于窄 带干扰引起的虚警率， 且具有低复杂度的优点。 附图概述
图 1 为本发明的具体实施方式提供的基于增强型频谱相关函数的无线麦克 风信号检测方法的流程示意图；
图 2为本发明的实施例 1中 MATLAB模拟产生的无线麦克风信号的增强型频
谱相关函数模的三维图， 其中 = 5, = -17, s = 0.1, r2 = 1；
图 3为本发明的实施例 1中 MATLAB模拟产生连续波窄带干扰的增强型频谱 相关函数幅值的三维图， 其中 SVR = -17, κλ = 0.1, r2 = l ;
图 4为本发明的实施例 1 中当 ^ = 2时不同 SN ?下， 基于增强型频谱相关函 数感知方法的 R0C性能曲线图；
图 5为本发明的实施例 1中当 SN ? = -23时不同 ^下， 基于增强型频谱相关函 数感知方法的 R0C性能曲线图；
图 6为本发明的实施例 2中无线麦克风信号感知流程框图；
图 7为本发明的实施例 2中根据图 6中描述的实验流程获取的无线麦克风信 号， 并由公式（6)计算得到的增强型频谱相关函数幅值的三维图；
图 8为本发明的实施例 2中根据图 6中描述的实验流程获取的窄带干扰， 并由公式（6)计算得到的增强型频谱相关函数幅值的三维图。 本发明的最佳实施方案
本具体实施方式提供了一种基于增强型频谱相关函数的无线麦克风信号检 测方法， 如图 1所示， 包括：
步骤 1， 通过天线模块接收空中信号；
步骤 2， 对接收到的信号进行低噪声放大；
步骤 3， 对放大后的信号进行带通滤波；
步骤 4， 根据需要可以将滤波出来的信号进行正交下变频到中频或基带； 步骤 5， 对正交下变频器出来的 IQ两路信号进行低通滤波；
步骤 6， 将低通滤波器出来的信号送入到增益控制器中进行增益调整； 步骤 7， 将增益调整后的信号送入到模数转换器中进行模数转化； 步骤 8， 将模数转换出来的数字信号送入时域信号处理模块， 在该模块中完 成对信号的接收、 下采样、 下变频、 IQ 合并以及存储等处理， 进而得到检测所 需的 M段不重叠或部分重叠的时域数字信号；
步骤 9， 扫描所述时域数字信号， 获得待检测频点。
步骤 10， 根据式 （2 ) 计算待检测频点数字信号频谱相关函数；
步骤 11， 根据式 （3) 计算待检测频点数字信号的共轭频谱相关函数； 步骤 12， 根据式 （1) 获得待检测频点数字信号的增强型频谱相关函数； 步骤 13， 利用判决理论， 例如根据式 （4) 计算获得判决统计量 7；;
步骤 14， 通过预定方法模拟或计算获得门限值 Y ;
步骤 15， 根据 7；与 γ 的比较结果给出判决， 即如果 7； < γ, 则为窄带干扰， 否则为无线麦克风信号。
具体的， 本具体实施方式提出共轭频谱相关函数， 并结合频谱相关函数形成 增强型频谱相关函数，从而建立了一种基于增强型频谱相关函数的无线麦克风信 号感知方法， 利用增强型频谱相关函数的特征来正确区分正弦连续波 (模拟窄带 干扰）和无线麦克风信号， 从而准确判决当前信道有无无线麦克风信号， 为电视 空白频段的有效和充分利用奠定基础。
首先将天线模块 101接收到的信号送到低噪声放大器（LNA) 102， 放大信号 经过带通滤波器（BPF) 103， 其带宽可以根据实际需要进行调整， 接着将滤波后 的信号送入正交下变频器 105， 以所选电视频段内的频点作为本振 104频率对信 号进行下正交变频处理， 进而得到 IQ两路信号， 然后让两路信号分别通过一定 带宽的低通滤波 （LPF) 106和中频放大器 （IF Amp) 107并将中放出来的 IQ两 路信号送入到模数转换器 （ADC) 109中， 最后将 ADC109出来的两路数字信号送 入 FPGA110中， 在 FPGA110中完成对信号的接收、 下采样、 下变频、 IQ合并以 及存储等处理， 进而我们获得了检测所需的时域数字信号。用正弦连续波信号模 拟窄带干扰， 可以建立二元假设模型：
H, (无线麦克风信号）： χ[η] = ^β](2π^"Τ,,η(τ)ί1τ+φ) + ω[η (1)
H2(正弦连续波信号）： χ[η] = ^-ε^ + ω[η], (2) 其中， ]表示带限复高斯噪声， 其方差为 σ2， 易得信噪比为 VRz / iT2;) 对于给定数字信号 x[«],« = l,2,...,N-l， 频谱相关函数（SCF)的计算公式为：
Λ 1 (M_l)/2
x 副 k__- N I1 N 2
其中， M是一个正的奇数且 M≤N。 为 χ[·]的离散时间傅里叶变换（DTFT)
X(f) =∑x[n]e-J2^, (4) 当公式（3)中的 / ± «/ 2是 1 / N的整数倍时， 可通过快速傅里叶变换（FFT)计 算;^ /)。 此方法计算得到的频谱相关函数不能有效的展示无线麦克风信号的独 特特征， 因此本具体实施方式提出共轭频谱相关函数 并在此基础上结合 原频谱相关函数构造增强型频谱相关函数 σ)。。 σλ的定义如下：
由此得到的增强型频谱相关函数 。定义为：
sAa f)a = ^Xif) +K2s {f)c L (6) 无线麦克风信号和正弦连续波信号的增强型频谱相关函数具有不同的特征， 为了从数值上体现其差异， 可以采用如下检验统计量：
其中， Ψ是 l ^ AJ中频率 的取值范围， 而 Ω是 i ^o j中循环频率" 的取值范围。 本方法不用计算出整个 平面上 SCF的幅值， 而是通过一组有 限频率集上的增强型频谱相关函数幅值来计算统计量， 从而降低计算复杂度。
对于正弦连续波信号， ；相对较小； 而对于无线麦克风信号， ；相对较大 。 通过蒙特卡洛方法模拟得到特定虚警率下的判决门限 ^。 对于设定的门限 ^判 决准则如下：
如果 7 ≤ ， 则为窄带干扰信号， 否则为无线麦克风信号 （8) 下面结合说明书附图对本具体实施方式提供的制备方法的原理及功能进行 介绍。
实施例 1
本实施例阐述了基于增强型频谱相关函数的无线麦克风检测方法的系统仿
真。 仿真是基于 MATLAB环境下进行的， 具体仿真步骤如下：
1. 根据式（1)产生无线麦克风信号 x[«],« = l,2,...,N-l。 并对该信号作快速傅里 叶变换 (FFT)得到频域序列 X[K],K=\,2,...,N-\ o
2. 选择合适的频率和循环频率取值范围 Ψ和 Ω， 根据式（6)计算选定范围内的 增强型频谱相关函数。
3. 根据式 (7)计算检验统计量， 并与设定的门限值比较， 根据式 (8)的判决准则 做出判决。
其中的门限值计算方法为：由蒙特卡洛方法仿真得到不同信噪比下正弦连续 波信号的检验统计量的统计分布特性， 然后在给定的虚警率下求取门限值。
附图 2和图 3分别描述了无线麦克风信号和正弦连续波信号的增强型频谱相 关函数的三维图。可以从视觉上看到两者的区别， 无线麦克风信号的增强型频谱 相关函数在 = 0， 频率范围 Ψ内的幅值大于在/ = 0， 循环频率范围 Ω内的值； 而正弦连续波信号则恰好相反。
附图 4和图 5展示了由不同参数下应用增强型频谱相关函数检测无线麦克风 信号的性能。可以看到， 信噪比高于 -23dB时， 对于 大于 2的无线麦克风信号， 误警率极低。
实施例 2
本实施例阐述了基于周期图无线麦克风检测方法的实际系统实现。实际系统 架构 1如附图 6所示： 将天线模块 101接收到的信号送到低噪声放大器 (LNA) 102， 放大信号经过带通滤波器（BPF) 103， 其带宽可以根据实际需要进行调整， 接着将滤波后的信号送入正交下变频器 105， 以所选电视频段内的频点作为本振 104频率对信号进行正交下变频处理， 进而得到 IQ两路信号， 然后让两路信号 分别通过一定带宽的低通滤波 （LPF) 106和中频放大器 （IF Amp) 107并将中放 出来的 IQ两路信号送入到模数转换器 （ADC) 109中， 最后将 ADC109出来的两 路数字信号送入 FPGA110中，在 FPGA110中完成对信号的接收、下采样、下变频、 IQ 合并以及存储等处理， 进而我们获得了检测所需的时域数字信号， 通过 USB 等接口将数据送入 PC111中， 在 PC111中运行频域麦克风检测算法， 最后根据判 决结果对当前电视频段状况做出判断。对于不同的下变频频率和采样率可以通过
FPGA到本振和 ADC的反馈回路进行控制。 同时也可采用如附图 7所示的系统构 架 2， 该架构将架构 1 中的 PC111模块换成了以 DSP113为核心的模块， 该模块 将 FPGA110来的数据通过相应的接口如 EMIF口送入到数据存储器 114中， DSP113 实时地从存储器 114中读取数据完成频域麦克风检测算法并给出判决结果，对于 判决结果可以送到与 DSP相连的外设 112中，也可以通过一些接口如 USB口 115、 网口 116等传输到其他设备中。
基于架构 1的实际算法测试步骤如下：
1 ) 选择某个电视频段， 分别用无线麦克风信号发生器和信号发生器在不 同的频点产生麦克风信号和正弦连续波信号。
2 ) 运用如图 6架构的系统对信号进行采集，连续采集 i段时域数字信号， 每段的持续时间为 t ms。
3 ) 在 PC中用频域麦克风检测算法对得到的数据进行处理。
基于架构 2的实际算法测试步骤如下：
1) 选择某个电视频段， 分别用无线麦克风信号发生器和信号发生器在不同 的频点产生麦克风信号和正弦连续波信号。
2) 运用如图 7架构的系统对信号进行采集， 连续采集 i段时域数字信号， 每段的持续时间为 t ms。
3) 在 DSP芯片中用频域麦克风检测算法对得到的数据进行处理。
图 8和图 9分别展示了上述过程中实测无线麦克风信号和窄带干扰的增强型 频谱相关函数幅值的三维图， 实验结果与系统仿真结果基本一致。
本具体实施方式提供的技术方案基于增强型频谱相关函数的无线麦克风信 号感知方法， 能有效区分窄带干扰和无线麦克风信号， 从而解决了无法将窄带干 扰与无线麦克风信号进行区分的问题，使得当前空白电视频段检测中的重大难题 得到了解决， 同时本检测方法具有低算法复杂度， 在实际系统中易于实现。
本具体实施方式还提供了一种基于增强型频谱相关函数的无线信号检测装 置 ， 包括天线模块、 低噪声放大器、 带通滤波器、 下变频至中频或基带、 低通 滤波器、模数转换器和时域信号预处理模块， 天线模块的信号输出端与低噪音放 大器的信号输入端连接，低噪音放大器的信号输出端与带通滤波器的信号输入端
连接， 带通滤波器的信号输出端与下变频至中频或基带的信号输入端连接， 下变 频至中频或基带的信号输出端与低通滤波器的信号输入短连接，低通滤波器的信 号输出端与模数控制器的信号输入端连接，模数控制器的信号输出端时域信号预 处理模块的信号输入端连接。
可选的， 所述天线模块为甚高频和特高频频段接收天线， 所述下变频至中频 或基带包括根据要检测的电视频段设置本振的频率，通过正交下变频器将信号下 变频至中频或基带。
可选的， 所述低通滤波器的带宽需大于或等于一个电视频段带宽的一半， 所 述增益控制器包括根据模数转换器所需的电压或电流能手动或自动调整输出电 压值或电流值， 所述时域信号预处理模块用于通过可编程芯片实现两大功能：一 是对 IQ两路信号的接收、 下采样、 下变频、 合并以及存储等处理； 二是为其他 模块如本振、 模数转换器、 USB芯片等提供所需的控制信号。
上述基于增强型频谱相关函数的无线信号检测装置中涉及的各器件实现的 功能已经在之前的方法实施方式中详细描述， 故在此不再敷述。
以上所述， 仅为本发明较佳的具体实施方式， 但本发明的保护范围并不局限于 此， 任何熟悉本技术领域的技术人员在本发明揭露的技术范围内， 可轻易想到的变 化或替换， 都应涵盖在本发明的保护范围之内。 因此， 本发明的保护范围应该以权 利要求书的保护范围为准。
Claims
1、 一种基于增强型频谱相关函数的无线信号检测方法， 其特征在于， 包括： 获得预处理的时域数字信号 χ[«]，并计算获得所述数字信号 χ[«]的频谱相关函 数 (/)， 以及计算获得所述数字信号的共轭频谱相关函数 并获得所述 数字信号 χ[«]的增强型频谱相关函数 ；
计算获得数字信号 x[«]的检验统计量 7；， 通过预定方法模拟或计算获得门限 值 Υ， 根据所述检验统计量 7 与门限值 γ 的比较结果判决获得的时域数字信号 x[«]是否为无线麦克风信号。
2、 根据权利要求 1所述的方法， 其特征在于， 计算所述数字信号的频谱相 关函数。
3、 根据权利要求 1所述的方法， 其特征在于， 计算所述数字信号的共轭频 谱相关函数。
4、 根据权利要求 1所述的方法， 其特征在于， 获得所述数字信号的增强型 频谱相关函数。
5、 根据权利要求 1 所述的方法， 其特征在于， 计算获得所述数字信号的检 验统计量。
6、 根据权利要求 1 所述的方法， 其特征在于， 通过预定方法模拟或计算获 得门限值 Y， 包括采用蒙特卡罗法模拟出门限值或者根据实际数据设置出门限 值。
7、 根据权利要求 1所述的方法， 其特征在于， 根据 7；与 Υ 的比较结果给出 判决， 如果 7 < γ , 则为窄带干扰， 否则为无线麦克风信号。
8、 一种基于增强型频谱相关函数的无线信号检测装置， 包括天线模块、 低 噪声放大器、 带通滤波器、 下变频至中频或基带、 低通滤波器、 模数转换器和时 域信号预处理模块， 其特征在于， 天线模块的信号输出端与低噪音放大器的信号 输入端连接， 低噪音放大器的信号输出端与带通滤波器的信号输入端连接， 带通 滤波器的信号输出端与下变频至中频或基带的信号输入端连接，下变频至中频或 基带的信号输出端与低通滤波器的信号输入短连接，低通滤波器的信号输出端与 模数控制器的信号输入端连接，模数控制器的信号输出端时域信号预处理模块的 信号输入端连接。
9、 根据权利要求 8所述的装置， 其特征在于， 所述天线模块为甚高频和特 高频频段接收天线，所述下变频至中频或基带包括根据要检测的电视频段设置本 振的频率， 通过正交下变频器将信号下变频至中频或基带。
10、 根据权利要求 8所述的装置， 其特征在于， 所述低通滤波器的带宽需大 于或等于一个电视频段带宽的一半，所述增益控制器包括根据模数转换器所需的 电压或电流能手动或自动调整输出电压值或电流值，所述时域信号预处理模块用 于通过可编程芯片实现两大功能： 一是对 IQ两路信号的接收、 下采样、 下变频、 合并以及存储等处理； 二是为其他模块如本振、 模数转换器、 USB芯片等提供所 需的控制信号。
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