技术领域technical field
本发明涉及信号识别技术领域，特别是一种基于瞬时频率的FASST信号识别方法及装置。The invention relates to the technical field of signal identification, in particular to an instantaneous frequency-based FASST signal identification method and device.
背景技术Background technique
自动调制类型识别的基本任务就是在给定信道条件下，确定接收信号的调制方式，并给出相应的调制参数，为进一步分析和处理信号提供依据。在低信噪比和多径衰落失真条件下，如何有效提高信号识别性能是自动调制类型识别的关键问题。The basic task of automatic modulation type identification is to determine the modulation mode of the received signal under the given channel conditions, and provide the corresponding modulation parameters to provide a basis for further analysis and signal processing. Under the conditions of low signal-to-noise ratio and multipath fading distortion, how to effectively improve the performance of signal identification is the key issue of automatic modulation type identification.
针对特定协议的信号，传统的自动调制类型识别只能得到信号的调制方式和调制参数，无法确定信号的协议类型。同时，由于没有利用信号的先验信息，传统自动调制类型识别的性能难以提高。针对特定的协议信号，验证识别具有更好的识别性能。验证识别通过提取信号特征来验证待识别信号是否属于集合中的某一种信号，并且指出该信号的协议类型。FASST(Futaba Advanced SpreadSpectrum Technology)是日本双叶集团生产的遥控器的遥控信号，采用扩频加跳频的方式来避免不同遥控器之间的信号干扰。该信号在ISM频段使用，信号背景较为复杂，存在多种形式的干扰信号，采用跳频检测进行识别的方法容易受到干扰信号的影响，识别效果不好。对单跳信号的识别主要是对其调制方式进行识别，基于似然函数的识别方法主要从基带信号进行识别，需要已知信号的中心频率，当接收信号存在频率偏差时，容易受到此频率偏差的影响导致信号识别不准确。For a signal of a specific protocol, the traditional automatic modulation type identification can only obtain the modulation mode and modulation parameters of the signal, but cannot determine the protocol type of the signal. At the same time, it is difficult to improve the performance of traditional automatic modulation type recognition because the prior information of the signal is not used. For specific protocol signals, verification recognition has better recognition performance. Verification and identification verify whether the signal to be identified belongs to a certain signal in the set by extracting signal features, and point out the protocol type of the signal. FASST (Futaba Advanced SpreadSpectrum Technology) is the remote control signal of the remote control produced by Futaba Group in Japan. It uses spread spectrum and frequency hopping to avoid signal interference between different remote controls. The signal is used in the ISM frequency band, the signal background is relatively complex, and there are various forms of interference signals. The identification method using frequency hopping detection is easily affected by interference signals, and the identification effect is not good. The identification of the single-hop signal is mainly to identify its modulation mode. The identification method based on the likelihood function is mainly identified from the baseband signal, and the center frequency of the signal needs to be known. When there is a frequency deviation in the received signal, it is vulnerable to this frequency deviation. The influence of the signal leads to inaccurate signal recognition.
发明内容Contents of the invention
本发明的目的是提供一种基于瞬时频率的FASST信号识别方法及装置，用以解决接收信号频率偏差条件下无法对FASST信号进行准确识别的问题。The purpose of the present invention is to provide a method and device for identifying FASST signals based on instantaneous frequency to solve the problem that the FASST signals cannot be accurately identified under the condition of frequency deviation of received signals.
为了实现对FASST信号的快速识别，解决接收信号频率偏差条件下无法对FASST信号进行准确识别的问题，本发明提供一种基于瞬时频率的FASST信号识别方法，包括如下步骤：In order to realize the rapid identification of the FASST signal and solve the problem that the FASST signal cannot be accurately identified under the frequency deviation condition of the received signal, the present invention provides a method for identifying the FASST signal based on the instantaneous frequency, comprising the following steps:
1)采集设定长度的待处理信号数据，经过预处理将待处理信号数据转换为采样率与FASST信号的符号速率匹配的复信号；1) Collect the signal data to be processed with a set length, and convert the signal data to be processed into a complex signal whose sampling rate matches the symbol rate of the FASST signal through preprocessing;
2)采用瞬时自相关法计算复信号的归一化瞬时频率；2) Calculate the normalized instantaneous frequency of the complex signal by using the instantaneous autocorrelation method;
3)根据FASST信号的扩频码特性，将一个扩频码内0和1比特所对应的频率的所有归一化瞬时频率样点进行累加得到归一化瞬时频率累加和；3) According to the spreading code characteristics of the FASST signal, all the normalized instantaneous frequency samples of the frequencies corresponding to 0 and 1 bits in a spreading code are accumulated to obtain the normalized instantaneous frequency cumulative sum;
4)根据0和1比特对应的归一化瞬时频率累加和得到其零均值或1均值频率差的绝对值，并判断该绝对值的峰值特性是否满足第一设定峰值条件，若满足，则识别为FASST信号。4) Obtain the absolute value of the zero-mean or 1-mean frequency difference according to the cumulative sum of the normalized instantaneous frequencies corresponding to 0 and 1 bits, and judge whether the peak characteristic of the absolute value satisfies the first set peak condition, and if so, then Recognized as a FASST signal.
进一步地，为了提升抗噪声性能，步骤4)中得到绝对值后，还计算该绝对值的等间隔滑动累加和，并判断该等间隔滑动累加和的峰值是否满足第二设定峰值条件，若满足，则识别为FASST信号。Further, in order to improve the anti-noise performance, after the absolute value is obtained in step 4), the equal interval sliding accumulation sum of the absolute value is also calculated, and it is judged whether the peak value of the equal interval sliding accumulation sum satisfies the second set peak value condition, if If it is satisfied, it is recognized as a FASST signal.
进一步地，为了提高信号识别的准确度，所述第一设定峰值条件为峰值大小介于0.5倍频率间隔和两倍频率间隔之间，且存在连续16个间隔为扩频码长度的峰值。Further, in order to improve the accuracy of signal identification, the first set peak condition is that the peak size is between 0.5 times the frequency interval and twice the frequency interval, and there are 16 consecutive peaks whose interval is the length of the spreading code.
进一步地，为了提高信号识别的准确度，所述第二设定峰值条件为峰值大小介于M/2倍频率间隔和2M倍频率间隔之间，且存在连续16个间隔为扩频码长度的峰值，其中M为累加码元数。Further, in order to improve the accuracy of signal identification, the second set peak condition is that the peak size is between M/2 times the frequency interval and 2M times the frequency interval, and there are 16 consecutive intervals with the length of the spreading code Peak value, where M is the number of accumulated symbols.
进一步地，为了对采集的信号数据进行进一步地运算，所述预处理步骤如下：Further, in order to perform further operations on the collected signal data, the preprocessing steps are as follows:
(1)通过变频处理和滤波处理将待处理信号数据变换为零中频复信号；(1) Transform the signal data to be processed into a zero intermediate frequency complex signal by frequency conversion processing and filter processing;
(2)根据FASST信号的符号速率得到采样率，将待处理信号进行重采样处理转换为复信号。(2) The sampling rate is obtained according to the symbol rate of the FASST signal, and the signal to be processed is converted into a complex signal by resampling.
进一步地，为了实现对复信号的识别和提取，所述复信号的瞬时自相关表达式为：R(n,m)＝s*(n)s(n+m)＝A2exp(j2πfim)，其中A为信号的幅度，fi为载频，m为延迟间隔，且m＞0，通过瞬时自相关法提取，计算公式如下：Further, in order to realize the identification and extraction of the complex signal, the instantaneous autocorrelation expression of the complex signal is: R(n,m)=s* (n)s(n+m)=A2 exp(j2πfi m), where A is the amplitude of the signal, fi is the carrier frequency, m is the delay interval, and m>0, extracted by the instantaneous autocorrelation method, the calculation formula is as follows:
式中fs为信号的采样频率，当m＝1时得到归一化瞬时频率如下：In the formula, fs is the sampling frequency of the signal. When m=1, the normalized instantaneous frequency is obtained as follows:
finst(n)＝finst(n,1)/fs。finst (n)=finst (n,1)/fs .
进一步地，为了适用于FASST信号的识别，根据FASST信号的扩频码特性，FASST信号的扩频码为b0＝[00011101101]，b1＝[11100010010]，扩频码内第1到3比特、第7比特和第10比特对应瞬时频率f0，第4到6比特、第8比特、第11比特对应瞬时频率f1，对扩频码内0、1比特所对应的归一化瞬时频率进行累加，得到累加和的计算公式如下：Further, in order to be applicable to the identification of FASST signals, according to the characteristics of the spreading codes of the FASST signals, the spreading codes of the FASST signals are b0 =[00011101101], b1 =[11100010010], the first to third bits in the spreading code , the 7th bit and the 10th bit correspond to the instantaneous frequency f0 , the 4th to 6th bits, the 8th bit, and the 11th bit correspond to the instantaneous frequency f1 , and the normalized instantaneous frequency corresponding to the 0 and 1 bits in the spreading code Accumulation is carried out to obtain the calculation formula of accumulation sum as follows:
其中，P为过采样倍数。Among them, P is the oversampling multiple.
进一步地，为了消除载波频率偏差对归一化瞬时频率累加和的影响，并进一步提升抗噪声性能，步骤3)中归一化瞬时频率累加和的零均值频率差的绝对值为：Further, in order to eliminate the influence of the carrier frequency deviation on the normalized instantaneous frequency sum and further improve the anti-noise performance, the absolute value of the zero-mean frequency difference of the normalized instantaneous frequency sum in step 3) is:
df(n)＝|sf0(n)-fmean(n)|df(n)＝|sf0 (n)-fmean (n)|
其中，fmean(n)＝[sf0(n)+sf1(n)]/2。Wherein, fmean (n)=[sf0 (n)+sf1 (n)]/2.
进一步地，为了进一步提升抗噪声性能，每码元取1个样点的df(n)进行累加，累加码元数为M，即可得到df(n)的等间隔滑动累加和的计算公式如下：Further, in order to further improve the anti-noise performance, df(n) of 1 sample point is taken for each symbol for accumulation, and the number of accumulated symbols is M, and the calculation formula of equal interval sliding accumulation sum of df(n) can be obtained as follows :
本发明还提供一种基于瞬时频率的FASST信号识别装置，包括存储器、处理器以及存储在存储器中并可在处理器上运行的计算机程序，所述处理器执行所述程序时实现以下步骤：The present invention also provides a kind of FASST signal identification device based on instantaneous frequency, comprises memory, processor and is stored in the memory and can run on the computer program on processor, when described processor executes described program, realize following steps:
1)采集设定长度的待处理信号数据，经过预处理将待处理信号数据转换为采样率与FASST信号的符号速率匹配的复信号；1) Collect the signal data to be processed with a set length, and convert the signal data to be processed into a complex signal whose sampling rate matches the symbol rate of the FASST signal through preprocessing;
2)采用瞬时自相关法计算复信号的归一化瞬时频率；2) Calculate the normalized instantaneous frequency of the complex signal by using the instantaneous autocorrelation method;
3)根据FASST信号的扩频码特性，将一个扩频码内0和1比特所对应的频率的所有归一化瞬时频率样点进行累加得到归一化瞬时频率累加和；3) According to the spreading code characteristics of the FASST signal, all the normalized instantaneous frequency samples of the frequencies corresponding to 0 and 1 bits in a spreading code are accumulated to obtain the normalized instantaneous frequency cumulative sum;
4)根据0和1比特对应的归一化瞬时频率累加和得到其零均值或1均值频率差的绝对值，并判断该绝对值的峰值特性是否满足第一设定峰值条件，若满足，则识别为FASST信号。4) Obtain the absolute value of the zero-mean or 1-mean frequency difference according to the cumulative sum of the normalized instantaneous frequencies corresponding to 0 and 1 bits, and judge whether the peak characteristic of the absolute value satisfies the first set peak condition, and if so, then Recognized as a FASST signal.
进一步地，步骤4)中得到绝对值后，还计算该绝对值的等间隔滑动累加和，并判断该等间隔滑动累加和的峰值是否满足第二设定峰值条件，若满足，则识别为FASST信号。Further, after the absolute value is obtained in step 4), the equal interval sliding accumulation sum of the absolute value is also calculated, and it is judged whether the peak value of the equal interval sliding accumulation sum satisfies the second set peak value condition, and if so, it is identified as FASST Signal.
进一步地，所述第一设定峰值条件为峰值大小介于0.5倍频率间隔和两倍频率间隔之间，且存在连续16个间隔为扩频码长度的峰值。Further, the first peak setting condition is that the peak size is between 0.5 times the frequency interval and twice the frequency interval, and there are 16 consecutive peaks whose intervals are the length of the spreading code.
进一步地，所述第二设定峰值条件为峰值大小介于M/2倍频率间隔和2M倍频率间隔之间，且存在连续16个间隔为扩频码长度的峰值，其中M为累加码元数。Further, the second setting peak condition is that the peak size is between M/2 times the frequency interval and 2M times the frequency interval, and there are 16 consecutive peaks whose interval is the length of the spreading code, where M is the accumulated symbol number.
进一步地，所述预处理步骤如下：Further, the preprocessing steps are as follows:
(1)通过变频处理和滤波处理将待处理信号数据变换为零中频复信号；(1) Transform the signal data to be processed into a zero intermediate frequency complex signal by frequency conversion processing and filter processing;
(2)根据FASST信号的符号速率得到采样率，将待处理信号进行重采样处理转换为复信号。(2) The sampling rate is obtained according to the symbol rate of the FASST signal, and the signal to be processed is converted into a complex signal by resampling.
进一步地，为了实现对复信号的识别和提取，所述复信号的瞬时自相关表达式为：R(n,m)＝s*(n)s(n+m)＝A2exp(j2πfim)，其中A为信号的幅度，fi为载频，m为延迟间隔，且m＞0，通过瞬时自相关法提取，计算公式如下：Further, in order to realize the identification and extraction of the complex signal, the instantaneous autocorrelation expression of the complex signal is: R(n,m)=s* (n)s(n+m)=A2 exp(j2πfi m), where A is the amplitude of the signal, fi is the carrier frequency, m is the delay interval, and m>0, extracted by the instantaneous autocorrelation method, the calculation formula is as follows:
式中fs为信号的采样频率，当m＝1时得到归一化瞬时频率如下：In the formula, fs is the sampling frequency of the signal. When m=1, the normalized instantaneous frequency is obtained as follows:
finst(n)＝finst(n,1)/fs。finst (n)=finst (n,1)/fs .
进一步地，FASST信号的扩频码为b0＝[00011101101]，b1＝[11100010010]，扩频码内第1到3比特、第7比特和第10比特对应瞬时频率f0，第4到6比特、第8比特、第11比特对应瞬时频率f1，对扩频码内0、1比特所对应的归一化瞬时频率进行累加，得到累加和的计算公式如下：Further, the spreading code of the FASST signal is b0 =[00011101101], b1 =[11100010010], the first to third bits, the seventh bit and the tenth bit in the spreading code correspond to the instantaneous frequency f0 , the fourth to The 6th bit, the 8th bit, and the 11th bit correspond to the instantaneous frequency f1 , and the normalized instantaneous frequencies corresponding to the 0 and 1 bits in the spreading code are accumulated, and the formula for calculating the accumulated sum is as follows:
其中，P为过采样倍数。Among them, P is the oversampling multiple.
进一步地，步骤3)中归一化瞬时频率累加和的零均值频率差的绝对值为：Further, the absolute value of the zero-mean frequency difference of the normalized instantaneous frequency accumulation sum in step 3) is:
df(n)＝|sf0(n)-fmean(n)|df(n)＝|sf0 (n)-fmean (n)|
其中，fmean(n)＝[sf0(n)+sf1(n)]/2。Wherein, fmean (n)=[sf0 (n)+sf1 (n)]/2.
进一步地，为了进一步提升抗噪声性能，每码元取1个样点的df(n)进行累加，累加码元数为M，即可得到df(n)的等间隔滑动累加和的计算公式如下：Further, in order to further improve the anti-noise performance, df(n) of 1 sample point is taken for each symbol for accumulation, and the number of accumulated symbols is M, and the calculation formula of equal interval sliding accumulation sum of df(n) can be obtained as follows :
附图说明Description of drawings
图1是一种基于瞬时频率的FASST信号识别方法的流程图；Fig. 1 is a kind of flow chart of the FASST signal identification method based on instantaneous frequency;
图2是FASST信号的归一化瞬时频率的模拟结果图；Fig. 2 is the simulation result diagram of the normalized instantaneous frequency of the FASST signal;
图3是FASST信号的归一化瞬时频率累加和的模拟结果图；Fig. 3 is the simulation result diagram of the normalized instantaneous frequency accumulation sum of the FASST signal;
图4是FASST信号的归一化瞬时频率累加和的零均值频率差的绝对值的模拟结果图；Fig. 4 is the simulation result diagram of the absolute value of the zero-mean value frequency difference of the normalized instantaneous frequency cumulative sum of the FASST signal;
图5是FASST信号的零均值频率差的滑动累加和的模拟结果图；Fig. 5 is the simulation result figure of the sliding cumulative sum of the zero-mean frequency difference of the FASST signal;
图6是一种基于瞬时频率的FASST信号识别的改进方法的流程图。Fig. 6 is a flow chart of an improved method of FASST signal identification based on instantaneous frequency.
具体实施方式Detailed ways
下面结合附图对本发明做进一步详细的说明。The present invention will be described in further detail below in conjunction with the accompanying drawings.
本发明提供一种基于瞬时频率的FASST信号识别装置，包括存储器、处理器以及存储在存储器中并可在处理器上运行的计算机程序，该处理器执行程序时实现一种基于瞬时频率的FASST信号识别方法，如图1所示，包括如下步骤：The present invention provides a FASST signal identification device based on instantaneous frequency, which includes a memory, a processor and a computer program stored in the memory and operable on the processor, when the processor executes the program, a FASST signal based on instantaneous frequency is realized The identification method, as shown in Figure 1, includes the following steps:
1、采集一定长度的待处理信号数据，经过变频、滤波和重采样处理后转换为采样率与符号速率匹配的复信号s(n)。1. Collect a certain length of signal data to be processed, and convert it into a complex signal s(n) whose sampling rate matches the symbol rate after frequency conversion, filtering and resampling.
对采集的信号数据，需要经过变频处理和滤波处理使信号为零中频复信号，允许存在频率偏差。根据目标FASST信号的符号速率，选择合适的重采样速率，将待处理信号重采样为与目标FASST符号速率相匹配的复信号，使得每个FASST符号具有相同的整数个采样点，由于FASST信号采用FSK调制方式，通过重采样，使得每个FSK符号的过采样倍数为整数P。For the collected signal data, frequency conversion processing and filtering processing are required to make the signal a zero-IF complex signal, and frequency deviation is allowed. According to the symbol rate of the target FASST signal, select an appropriate resampling rate, resample the signal to be processed into a complex signal that matches the target FASST symbol rate, so that each FASST symbol has the same integer number of sampling points, because the FASST signal uses In the FSK modulation mode, through resampling, the oversampling multiple of each FSK symbol is an integer P.
2、计算复信号s(n)的归一化瞬时频率finst(n)。2. Calculate the normalized instantaneous frequency finst (n) of the complex signal s(n).
FASST信号的复基带信号即复信号s(n)可表示为：The complex baseband signal of the FASST signal, that is, the complex signal s(n), can be expressed as:
其中A为信号的幅度，为任意初相，fi为载频。该复信号的瞬时自相关可表示为：where A is the amplitude of the signal, is any initial phase, and fi is the carrier frequency. The instantaneous autocorrelation of this complex signal can be expressed as:
R(n,m)＝s*(n)s(n+m)＝A2exp(j2πfim)R(n,m)=s* (n)s(n+m)=A2 exp(j2πfi m)
其中m为延迟间隔，且m＞0。因此，该复信号s(n)的瞬时频率采用瞬时自相关法提取，计算公式如下：Where m is the delay interval, and m>0. Therefore, the instantaneous frequency of the complex signal s(n) is extracted by the instantaneous autocorrelation method, and the calculation formula is as follows:
其中fs为信号的采样频率。当m＝1时表示前后样点相位差得到的瞬时频率，对采样率归一化后得到归一化瞬时频率finst(n)：Where fs is the sampling frequency of the signal. When m=1, it represents the instantaneous frequency obtained by the phase difference between the front and rear sample points, and the normalized instantaneous frequency finst (n) is obtained after normalizing the sampling rate:
finst(n)＝finst(n,1)/fsfinst (n) = finst (n,1)/fs
从图2中可以看出，归一化瞬时频率的频率间隔为0.125。It can be seen from Figure 2 that the frequency interval of the normalized instantaneous frequency is 0.125.
3、根据FASST信号的扩频码特性，计算一个扩频码内0、1比特所对应的归一化瞬时频率累加和sf0(n)、sf1(n)。3. According to the spreading code characteristics of the FASST signal, calculate the normalized instantaneous frequency accumulation sums sf0 (n) and sf1 (n) corresponding to bits 0 and 1 in a spreading code.
FASST信号采用了直接序列扩频(DSSS)技术，其扩频码为b0＝[00011101101]，b1＝[11100010010]，原始信息比特经过扩频后每比特扩展为11比特序列，即原始信息比特0扩展为11比特b0，原始信息比特1扩展为11比特b1。经过FSK调制后，比特0对应f0，比特1对应f1。The FASST signal adopts Direct Sequence Spread Spectrum (DSSS) technology, and its spreading code is b0 = [00011101101], b1 = [11100010010], and each bit of the original information is expanded into an 11-bit sequence after spreading, that is, the original information Bit 0 is extended to 11 bits b0 , and bit 1 of the original information is extended to 11 bits b1 . After FSK modulation, bit 0 corresponds to f0 , and bit 1 corresponds to f1 .
根据上述扩频码，扩频码内第1到3比特、第7比特和第10比特对应瞬时频率f0，第4到6比特、第8比特、第11比特对应瞬时频率f1。为了适用于FASST信号的识别，对扩频码内0、1比特所对应的归一化瞬时频率进行累加，得到累加和的计算公式如下：According to the above spreading code, the 1st to 3rd bits, the 7th bit and the 10th bit in the spreading code correspond to the instantaneous frequency f0 , and the 4th to 6th bits, the 8th bit and the 11th bit correspond to the instantaneous frequency f1 . In order to be applicable to the identification of FASST signals, the normalized instantaneous frequencies corresponding to 0 and 1 bits in the spreading code are accumulated, and the calculation formula for the accumulated sum is as follows:
其中P为过采样倍数。Where P is the oversampling multiple.
如图3所示，累加后将在每个扩频码的起始位置出现峰值。As shown in Figure 3, a peak will appear at the starting position of each spreading code after accumulation.
4、计算归一化瞬时频率累加和的零均值频率差的绝对值df(n)，并判断该绝对值的峰值特性是否满足第一设定峰值条件，若满足，则识别为FASST信号。4. Calculate the absolute value df(n) of the zero-mean frequency difference of the normalized instantaneous frequency accumulation sum, and judge whether the peak characteristic of the absolute value satisfies the first set peak condition, and if so, identify it as a FASST signal.
由于复信号s(n)可能存在载波频率偏差，该频率偏差值位于f0和f1的中间，因此，可以通过求均值获得，即Since the complex signal s(n) may have a carrier frequency deviation, the frequency deviation value is located in the middle of f0 and f1 , so it can be obtained by averaging, that is
fmean(n)＝[sf0(n)+sf1(n)]/2fmean (n)＝[sf0 (n)+sf1 (n)]/2
为了消除载波频率偏差对归一化瞬时频率累加和的影响，使得累加和的峰值更加明显，按下式计算零均值频率差的绝对值df(n)：In order to eliminate the influence of the carrier frequency deviation on the normalized instantaneous frequency cumulative sum and make the peak value of the cumulative sum more obvious, the absolute value df(n) of the zero-mean frequency difference is calculated as follows:
df(n)＝|sf0(n)-fmean(n)|df(n)＝|sf0 (n)-fmean (n)|
如图4所示，为FASST信号归一化瞬时频率累加和的零均值频率差的绝对值的模拟结果图。还可以计算1均值频率差的绝对值即sf1(n)与平均值的差值的绝对值，由于效果相同，此处不再赘述。As shown in Figure 4, it is the simulation result diagram of the absolute value of the zero-mean frequency difference of the normalized instantaneous frequency accumulation sum of the FASST signal. It is also possible to calculate the absolute value of the frequency difference of 1 mean value, that is, the absolute value of the difference between sf1 (n) and the mean value. Since the effect is the same, details are not repeated here.
经过上述步骤，将对FASST信号的识别转化为对df(n)的峰值特性进行判决。df(n)在每个扩频码位置出现峰值，理论峰值大小为FSK频率间隔，两个峰值之间的间隔为扩频码长度即P×11。判决条件可设为：是否存在连续16个间隔为P×11的峰值，若存在则可判为FASST信号，其中峰值大小介于0.5倍频率间隔和两倍频率间隔之间。After the above steps, the identification of the FASST signal is transformed into the judgment of the peak characteristic of df(n). df(n) peaks at each spreading code position, the theoretical peak size is the FSK frequency interval, and the interval between two peaks is the spreading code length, ie P×11. The judgment condition can be set as follows: whether there are 16 consecutive peaks with an interval of P×11, if there are, it can be judged as a FASST signal, and the peak size is between 0.5 times the frequency interval and twice the frequency interval.
在上述步骤的基础上，进一步地，为了提升抗噪声性能，还包括步骤：On the basis of the above steps, further, in order to improve the anti-noise performance, steps are also included:
5、计算df(n)的等间隔滑动累加和sdf(n)。5. Calculate the equal interval sliding accumulation sum sdf(n) of df(n).
由于df(n)在每个扩频码位置出现峰值，理论峰值大小为FSK的频率间隔。为了进一步提升抗噪声性能，对df(n)做等间隔滑动累加，即每码元取1个样点的df(n)进行累加，累加码元数为M，公式如下：Since df(n) peaks at each spreading code position, the theoretical peak size is the frequency interval of FSK. In order to further improve the anti-noise performance, equal interval sliding accumulation is performed on df(n), that is, df(n) of 1 sample point is taken for each symbol for accumulation, and the number of accumulated symbols is M, and the formula is as follows:
M的选择可根据信号信噪比的情况进行选择，M越大，抑制噪声的能力越强，累加效果越好。累加的结果如图5所示，从图5中可以看出，累加后的峰值更加明显，且两个峰值之间的间隔为扩频码长度。The selection of M can be selected according to the signal-to-noise ratio. The larger M is, the stronger the ability to suppress noise and the better the accumulation effect. The result of accumulation is shown in Figure 5. It can be seen from Figure 5 that the peak value after accumulation is more obvious, and the interval between the two peak values is the length of the spreading code.
6、根据sdf(n)的峰值特性，设置合适的门限值进行判决，符合判决条件则识别出FASST信号，否则不是。6. According to the peak characteristic of sdf(n), set an appropriate threshold value for judgment, if the judgment condition is met, the FASST signal is recognized, otherwise it is not.
如图6所示，经过上述步骤，将对FASST信号的识别转化为对sdf(n)的峰值特性进行判决。sdf(n)在每个扩频码位置出现峰值，理论峰值大小为M倍的FSK频率间隔，两个峰值之间的间隔为扩频码长度即P×11。判决条件可设为：是否存在连续16个间隔为P×11的峰值，若存在则可判为FASST信号，其中峰值大小介于M/2倍频率间隔和2M倍频率间隔之间。As shown in Fig. 6, after the above steps, the identification of the FASST signal is transformed into the judgment of the peak characteristic of sdf(n). sdf(n) peaks at each spreading code position, the theoretical peak size is M times the FSK frequency interval, and the interval between two peaks is the spreading code length, ie P×11. The judgment condition can be set as: whether there are 16 consecutive peaks with an interval of P×11, and if there are, it can be judged as a FASST signal, where the peak size is between M/2 times the frequency interval and 2M times the frequency interval.
以上给出了本发明涉及的具体实施方式，但本发明不局限于所描述的实施方式。在本发明给出的思路下，采用对本领域技术人员而言容易想到的方式对上述实施例中的技术手段进行变换、替换、修改，并且起到的作用与本发明中的相应技术手段基本相同、实现的发明目的也基本相同，这样形成的技术方案是对上述实施例进行微调形成的，这种技术方案仍落入本发明的保护范围内。The specific embodiments related to the present invention are given above, but the present invention is not limited to the described embodiments. Under the idea given by the present invention, the technical means in the above-mentioned embodiments are transformed, replaced, and modified in ways that are easy for those skilled in the art, and the functions played are basically the same as those of the corresponding technical means in the present invention. 1. The purpose of the invention realized is also basically the same, and the technical solution formed in this way is formed by fine-tuning the above-mentioned embodiments, and this technical solution still falls within the protection scope of the present invention.
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| US8605830B2 (en)* | 2010-07-30 | 2013-12-10 | National Instruments Corporation | Blind carrier/timing recovery and detection of modulation scheme |
| US10775510B2 (en)* | 2016-06-06 | 2020-09-15 | Brian G. Agee | Blind despreading of civil GNSS signals for resilient PNT applications |
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