CN108832964B - A kind of FASST signal recognition method and device based on instantaneous frequency - Google Patents

A kind of FASST signal recognition method and device based on instantaneous frequency Download PDF

Info

Publication number
CN108832964B
CN108832964B CN201810798961.XA CN201810798961A CN108832964B CN 108832964 B CN108832964 B CN 108832964B CN 201810798961 A CN201810798961 A CN 201810798961A CN 108832964 B CN108832964 B CN 108832964B
Authority
CN
China
Prior art keywords
signal
fasst
frequency
instantaneous frequency
bit
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201810798961.XA
Other languages
Chinese (zh)
Other versions
CN108832964A (en
Inventor
吴迪
訾琳溁
胡涛
蒋腾
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Information Engineering University of PLA Strategic Support Force
Original Assignee
Information Engineering University of PLA Strategic Support Force
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Information Engineering University of PLA Strategic Support Force filed Critical Information Engineering University of PLA Strategic Support Force
Priority to CN201810798961.XA priority Critical patent/CN108832964B/en
Publication of CN108832964A publication Critical patent/CN108832964A/en
Application granted granted Critical
Publication of CN108832964B publication Critical patent/CN108832964B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B1/00Details 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
    • H04B1/69Spread spectrum techniques
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00Modulated-carrier systems
    • H04L27/18Phase-modulated carrier systems, i.e. using phase-shift keying
    • H04L27/20Modulator circuits; Transmitter circuits

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Complex Calculations (AREA)
  • Digital Transmission Methods That Use Modulated Carrier Waves (AREA)

Abstract

The present invention relates to blipology field, especially a kind of FASST signal recognition method and device based on instantaneous frequency.By the signal data to be processed of acquisition setting length, the matched complex signal of character rate of sample rate Yu FASST signal is converted by pretreatment;The normalization instantaneous frequency of complex signal is calculated using instantaneous correlation method;And according to the spreading code characteristic of FASST signal by all normalization instantaneous frequency sampling points of frequency corresponding to 0 and 1 bit in a spreading code added up to obtain normalization instantaneous frequency it is cumulative and;Its zero-mean frequency absolute value of the difference is added up and obtained according to the corresponding normalization instantaneous frequency of 0 and 1 bit, and judge whether the peak feature of the absolute value meets the first setting peak value condition, if meeting, then it is identified as FASST signal, realize the quick identification to FASST signal, method complexity is low, has good noiseproof feature, solves the problems, such as not accurately identifying FASST signal under the conditions of reception frequency deviation signal.

Description

A kind of FASST signal recognition method and device based on instantaneous frequency
Technical field
The present invention relates to blipology field, especially a kind of FASST signal recognition method based on instantaneous frequency And device.
Background technique
The basic task of automatic Modulation type identification is exactly under the given channel conditions, to determine the modulation methods for receiving signal Formula, and corresponding modulation parameter is provided, foundation is provided for further analysis and processing signal.It is lost in low signal-to-noise ratio and multipath fading Under the conditions of true, the critical issue that signal identification performance is automatic Modulation type identification how is effectively improved.
For the signal of specific protocol, traditional automatic Modulation type identification can only obtain the modulation system and modulation of signal Parameter can not determine the protocol type of signal.Simultaneously as not utilizing the prior information of signal, traditional automatic Modulation type The performance of identification is difficult to improve.For specific protocol signal, verifying identification has better recognition performance.Verifying is identified by Signal characteristic is extracted to verify a certain signal whether signal to be identified belongs in set, and points out the protocol class of the signal Type.FASST (Futaba Advanced SpreadSpectrum Technology) is the remote controler of Japanese double leaf group production Remote signal, avoid the signal interference between different remote by the way of spread spectrum plus frequency hopping.The signal is in ISM band Use, signal background is complex, there are the interference signal of diversified forms, using frequency hopping detection know method for distinguishing be easy by To the influence of interference signal, recognition effect is bad.The identification of single-hop signal mainly identifies its modulation system, is based on The recognition methods of likelihood function is mainly identified from baseband signal, and the centre frequency of known signal is needed, and is deposited when receiving signal In frequency departure, it is easy to be influenced to cause signal identification inaccurate by this frequency departure.
Summary of the invention
The object of the present invention is to provide a kind of FASST signal recognition method and device based on instantaneous frequency, to solve The problem of FASST signal can not being accurately identified under the conditions of reception frequency deviation signal.
In order to realize the quick identification to FASST signal, solve not believing FASST under the conditions of reception frequency deviation signal The problem of number being accurately identified, the present invention provides a kind of FASST signal recognition method based on instantaneous frequency, including walks as follows It is rapid:
1) signal data to be processed of acquisition setting length, is converted to sample rate for signal data to be processed by pretreatment With the matched complex signal of character rate of FASST signal;
2) the normalization instantaneous frequency of complex signal is calculated using instantaneous correlation method;
3) according to the spreading code characteristic of FASST signal, by all of frequency corresponding to 0 and 1 bit in a spreading code Normalization instantaneous frequency sampling point add up to obtain normalization instantaneous frequency it is cumulative with;
4) cumulative according to the corresponding normalization instantaneous frequency of 0 and 1 bit and obtain the exhausted of its zero-mean or 1 means frequency difference To value, and judge whether the peak feature of the absolute value meets the first setting peak value condition, if satisfied, being then identified as FASST letter Number.
Further, in order to promote noise robustness, after obtaining absolute value in step 4), between the grade for also calculating the absolute value Every sliding it is cumulative and, and judge that this slide whether the peak value for the sum that adds up meets the second setting peak value condition at equal intervals, if satisfied, then It is identified as FASST signal.
Further, in order to improve the accuracy of signal identification, described first set peak value condition as peak value size between Between 0.5 overtones band interval and doubled frequency interval, and there are the peak values that spread code length is divided between continuous 16.
Further, in order to improve the accuracy of signal identification, described second set peak value condition as peak value size between Between M/2 overtones band interval and 2M overtones band interval, and there are the peak value for being divided into spread code length between continuous 16, wherein M is Cumulative code element number.
Further, in order to carry out further operation to the signal data of acquisition, the pre-treatment step is as follows:
(1) signal data to be processed is transformed to by zero intermediate frequency complex signal by frequency-conversion processing and filtering processing;
(2) sample rate is obtained according to the character rate of FASST signal, signal to be processed is subjected to resampling processing and is converted to Complex signal.
Further, in order to realize the identification and extraction to complex signal, the instantaneous auto-correlation expression formula of the complex signal are as follows: R (n, m)=s*(n) s (n+m)=A2exp(j2πfiM), wherein A be signal amplitude, fiFor carrier frequency, m is delay interval, and m > 0 is extracted by instantaneous correlation method, and calculation formula is as follows:
F in formulasFor the sample frequency of signal, it is as follows that normalization instantaneous frequency is obtained as m=1:
finst(n)=finst(n,1)/fs
Further, for the identification suitable for FASST signal, according to the spreading code characteristic of FASST signal, FASST letter Number spreading code be b0=[00011101101], b1=[11100010010], the 1 to 3rd bit, the 7th bit and in spreading code 10 bits correspond to instantaneous frequency f0, the 4 to 6th bit, the 8th bit, the 11st bit correspond to instantaneous frequency f1, to 0,1 ratio in spreading code Normalization instantaneous frequency corresponding to spy adds up, and the calculation formula for the sum that added up is as follows:
Wherein, P is over-sampling multiple.
Further, it in order to eliminate influence of the carrier frequency offset to the cumulative sum of normalization instantaneous frequency, and further mentions Noise robustness is risen, the zero-mean frequency absolute value of the difference of the cumulative sum of normalization instantaneous frequency in step 3) are as follows:
Df (n)=| sf0(n)-fmean(n)|
Wherein, fmean(n)=[sf0(n)+sf1(n)]/2。
Further, in order to further enhance noise robustness, every symbol takes the df (n) of 1 sampling point to add up, and adds up Code element number is M, and the calculation formula for sliding cumulative sum at equal intervals that df (n) can be obtained is as follows:
The present invention also provides a kind of FASST signal recognition device based on instantaneous frequency, including memory, processor and The computer program that can be run in memory and on a processor is stored, the processor is realized following when executing described program Step:
1) signal data to be processed of acquisition setting length, is converted to sample rate for signal data to be processed by pretreatment With the matched complex signal of character rate of FASST signal;
2) the normalization instantaneous frequency of complex signal is calculated using instantaneous correlation method;
3) according to the spreading code characteristic of FASST signal, by all of frequency corresponding to 0 and 1 bit in a spreading code Normalization instantaneous frequency sampling point add up to obtain normalization instantaneous frequency it is cumulative with;
4) cumulative according to the corresponding normalization instantaneous frequency of 0 and 1 bit and obtain the exhausted of its zero-mean or 1 means frequency difference To value, and judge whether the peak feature of the absolute value meets the first setting peak value condition, if satisfied, being then identified as FASST letter Number.
Further, after obtaining absolute value in step 4), also calculate the absolute value sliding at equal intervals it is cumulative and, and judge Whether the peak value for sliding cumulative sum at equal intervals meets the second setting peak value condition, if satisfied, being then identified as FASST signal.
Further, described first to set peak value condition be peak value size between 0.5 overtones band interval and doubled frequency Between, and there are the peak values that spread code length is divided between continuous 16.
Further, described second to set peak value condition be peak value size between M/2 overtones band interval and 2M overtones band Between, and there are the peak values that spread code length is divided between continuous 16, and wherein M is cumulative code element number.
Further, the pre-treatment step is as follows:
(1) signal data to be processed is transformed to by zero intermediate frequency complex signal by frequency-conversion processing and filtering processing;
(2) sample rate is obtained according to the character rate of FASST signal, signal to be processed is subjected to resampling processing and is converted to Complex signal.
Further, in order to realize the identification and extraction to complex signal, the instantaneous auto-correlation expression formula of the complex signal are as follows: R (n, m)=s*(n) s (n+m)=A2exp(j2πfiM), wherein A be signal amplitude, fiFor carrier frequency, m is delay interval, and m > 0 is extracted by instantaneous correlation method, and calculation formula is as follows:
F in formulasFor the sample frequency of signal, it is as follows that normalization instantaneous frequency is obtained as m=1:
finst(n)=finst(n,1)/fs
Further, the spreading code of FASST signal is b0=[00011101101], b1=[11100010010], spreading code Interior 1 to 3rd bit, the 7th bit and the 10th bit correspond to instantaneous frequency f0, the 4 to 6th bit, the 8th bit, the 11st bit are corresponding Instantaneous frequency f1, add up to normalization instantaneous frequency corresponding to 0,1 bit in spreading code, the calculating for the sum that added up is public Formula is as follows:
Wherein, P is over-sampling multiple.
Further, the zero-mean frequency absolute value of the difference of the cumulative sum of instantaneous frequency is normalized in step 3) are as follows:
Df (n)=| sf0(n)-fmean(n)|
Wherein, fmean(n)=[sf0(n)+sf1(n)]/2。
Further, in order to further enhance noise robustness, every symbol takes the df (n) of 1 sampling point to add up, and adds up Code element number is M, and the calculation formula for sliding cumulative sum at equal intervals that df (n) can be obtained is as follows:
Detailed description of the invention
Fig. 1 is a kind of flow chart of FASST signal recognition method based on instantaneous frequency;
Fig. 2 is the analog result figure of the normalization instantaneous frequency of FASST signal;
Fig. 3 is the analog result figure of the cumulative sum of normalization instantaneous frequency of FASST signal;
Fig. 4 is the analog result of the zero-mean frequency absolute value of the difference of the cumulative sum of normalization instantaneous frequency of FASST signal Figure;
Fig. 5 is the analog result figure of the cumulative sum of sliding of the zero-mean difference on the frequency of FASST signal;
Fig. 6 is a kind of flow chart of the improved method of FASST signal identification based on instantaneous frequency.
Specific embodiment
The present invention will be further described in detail with reference to the accompanying drawing.
The present invention provides a kind of FASST signal recognition device based on instantaneous frequency, including memory, processor and deposits The computer program that can be run in memory and on a processor is stored up, which realizes a kind of based on instantaneous when executing program The FASST signal recognition method of frequency, as shown in Figure 1, including the following steps:
1, the signal data to be processed for acquiring certain length is converted to sampling after frequency conversion, filtering and resampling processing Rate and the matched complex signal s (n) of character rate.
It to the signal data of acquisition, needs to make signal zero intermediate frequency complex signal by frequency-conversion processing and filtering processing, allow There are frequency departures.According to the character rate of target FASST signal, suitable resampling rate is selected, by signal weight to be processed It is sampled as the complex signal to match with target FASST character rate, so that the integer sampling having the same of each FASST symbol Point, since FASST signal uses FSK modulation mode, by resampling, so that the over-sampling multiple of each FSK symbol is integer P。
2, the normalization instantaneous frequency f of complex signal s (n) is calculatedinst(n)。
Complex baseband signal, that is, complex signal s (n) of FASST signal may be expressed as:
Wherein A is the amplitude of signal,For any first phase, fiFor carrier frequency.The instantaneous auto-correlation of the complex signal may be expressed as:
R (n, m)=s*(n) s (n+m)=A2exp(j2πfim)
Wherein m is delay interval, and m > 0.Therefore, the instantaneous frequency of the complex signal s (n) is mentioned using instantaneous correlation method It takes, calculation formula is as follows:
Wherein fsFor the sample frequency of signal.Sampling point phase difference obtained instantaneous frequency in front and back is indicated as m=1, to adopting Normalization instantaneous frequency f is obtained after the normalization of sample rateinst(n):
finst(n)=finst(n,1)/fs
From figure 2 it can be seen that the frequency interval of normalization instantaneous frequency is 0.125.
3, according to the spreading code characteristic of FASST signal, it is instantaneous to calculate normalization corresponding to 0,1 bit in a spreading code Frequency adds up and sf0(n)、sf1(n)。
FASST signal uses Direct Sequence Spread Spectrum (DSSS) technology, spreading code b0=[00011101101], b1= [11100010010], original information bits every bit expanded after spread spectrum is 11 bit sequences, i.e. original information bits 0 expand Exhibition is 11 bit b0, original information bits 1 are extended to 11 bit b1.After FSK modulation, the corresponding f of bit 00, the correspondence of bit 1 f1
According to above-mentioned spreading code, the 1 to 3rd bit, the 7th bit and the 10th bit correspond to instantaneous frequency f in spreading code0, the 4th Instantaneous frequency f is corresponded to 6 bits, the 8th bit, the 11st bit1.In order to be suitable for FASST signal identification, to 0 in spreading code, Normalization instantaneous frequency corresponding to 1 bit adds up, and the calculation formula for the sum that added up is as follows:
Wherein P is over-sampling multiple.
As shown in figure 3, peak value will occur in the initial position of each spreading code after cumulative.
4, the zero-mean frequency absolute value of the difference df (n) of the cumulative sum of normalization instantaneous frequency is calculated, and judges the absolute value Peak feature whether meet the first setting peak value condition, if satisfied, being then identified as FASST signal.
Since complex signal s (n) is there may be carrier frequency offset, which is located at f0And f1Centre, therefore, It can be obtained by averaging, i.e.,
fmean(n)=[sf0(n)+sf1(n)]/2
In order to eliminate influence of the carrier frequency offset to the cumulative sum of normalization instantaneous frequency, so that the peak value of cumulative sum is more Obviously, zero-mean frequency absolute value of the difference df (n) is calculated as follows:
Df (n)=| sf0(n)-fmean(n)|
As shown in figure 4, the simulation of the zero-mean frequency absolute value of the difference for the cumulative sum of FASST signal normalization instantaneous frequency Result figure.The 1 i.e. sf of means frequency absolute value of the difference can also be calculated1(n) with the absolute value of the difference of average value, due to effect phase Together, details are not described herein again.
By above-mentioned steps, the peak feature of df (n) is made decisions by being converted into the identification of FASST signal.df(n) There is peak value in each code position, theoretical peak size is FSK frequency interval, between two peak values between be divided into spreading code Length, that is, P × 11.Judgment condition can be set as: with the presence or absence of the peak value for being divided into P × 11 between continuous 16, can be then judged to if it exists FASST signal, wherein peak value size is between 0.5 overtones band interval and doubled frequency interval.
On the basis of above-mentioned steps, further, in order to promote noise robustness, further comprise the steps of:
5, the sliding at equal intervals for calculating df (n) adds up and sdf (n).
Since df (n) peak value occurs in each code position, theoretical peak size is the frequency interval of FSK.In order into One step promotes noise robustness, does sliding at equal intervals to df (n) and adds up, i.e., every symbol takes the df (n) of 1 sampling point to add up, Cumulative code element number is M, and formula is as follows:
The selection of M can be selected according to the case where Signal-to-Noise, and M is bigger, inhibit the ability of noise stronger, and add up effect Fruit is better.Accumulated result as shown in figure 5, from figure 5 it can be seen that the peak value after cumulative is more obvious, and two peak values it Between between be divided into spread code length.
6, according to the peak feature of sdf (n), suitable threshold value is set and is made decisions, meets judgment condition and then identifies Otherwise FASST signal is not.
As shown in fig. 6, by above-mentioned steps, by the identification of FASST signal be converted into the peak feature of sdf (n) into Row judgement.There are peak value, the FSK frequency interval that theoretical peak size is M times, two peak values in each code position in sdf (n) Between between be divided into spread code length i.e. P × 11.Judgment condition can be set as: with the presence or absence of the peak for being divided into P × 11 between continuous 16 Value, can then be judged to FASST signal, wherein peak value size is between M/2 overtones band interval and 2M overtones band interval if it exists.
Specific embodiment of the present invention is presented above, but the present invention is not limited to described embodiment. Under the thinking that the present invention provides, to the skill in above-described embodiment by the way of being readily apparent that those skilled in the art Art means are converted, are replaced, are modified, and play the role of with the present invention in relevant art means it is essentially identical, realize Goal of the invention it is also essentially identical, the technical solution formed in this way is to be finely adjusted to be formed to above-described embodiment, this technology Scheme is still fallen in protection scope of the present invention.

Claims (18)

1. a kind of FASST signal recognition method based on instantaneous frequency, which comprises the steps of:
1) acquisition setting length signal data to be processed, by pretreatment by signal data to be processed be converted to sample rate with The matched complex signal of the character rate of FASST signal;
2) the normalization instantaneous frequency of complex signal is calculated using instantaneous correlation method;
3) according to the spreading code characteristic of FASST signal, by all normalizings of frequency corresponding to 0 and 1 bit in a spreading code Change instantaneous frequency sampling point add up to obtain normalization instantaneous frequency it is cumulative with;
4) cumulative according to the corresponding normalization instantaneous frequency of 0 and 1 bit and obtain the absolute of its zero-mean or 1 means frequency difference Value, and judge whether the peak feature of the absolute value meets the first setting peak value condition, if satisfied, being then identified as FASST signal.
2. the FASST signal recognition method according to claim 1 based on instantaneous frequency, which is characterized in that in step 4) After obtaining absolute value, also calculate the absolute value sliding at equal intervals it is cumulative and, and judge that this slide the peak value for the sum that adds up at equal intervals Whether second setting peak value condition is met, if satisfied, being then identified as FASST signal.
3. the FASST signal recognition method according to claim 1 based on instantaneous frequency, which is characterized in that described first Setting peak value condition is peak value size between 0.5 overtones band interval and doubled frequency interval, and there are continuous 16 intervals For the peak value of spread code length.
4. the FASST signal recognition method according to claim 2 based on instantaneous frequency, which is characterized in that described second Setting peak value condition is peak value size between M/2 overtones band interval and 2M overtones band interval, and there are continuous 16 intervals For the peak value of spread code length, wherein M is cumulative code element number.
5. the FASST signal recognition method according to claim 1,2,3 or 4 based on instantaneous frequency, which is characterized in that institute It is as follows to state pre-treatment step:
(1) signal data to be processed is transformed to by zero intermediate frequency complex signal by frequency-conversion processing and filtering processing;
(2) sample rate is obtained according to the character rate of FASST signal, signal to be processed is subjected to resampling processing and is converted to letter in reply Number.
6. the FASST signal recognition method according to claim 5 based on instantaneous frequency, which is characterized in that the letter in reply Number instantaneous auto-correlation expression formula are as follows: R (n, m)=s*(n) s (n+m)=A2 exp(j2πfiM), wherein A be signal amplitude, fiFor carrier frequency, m is delay interval, and m > 0, is extracted by instantaneous correlation method, calculation formula is as follows:
F in formulasFor the sample frequency of signal, it is as follows that normalization instantaneous frequency is obtained as m=1:
finst(n)=finst(n,1)/fs
7. the FASST signal recognition method according to claim 6 based on instantaneous frequency, which is characterized in that FASST signal Spreading code be b0=[00011101101], b1=[11100010010], the 1 to 3rd bit, the 7th bit and the 10th in spreading code Bit corresponds to instantaneous frequency f0, the 4 to 6th bit, the 8th bit, the 11st bit correspond to instantaneous frequency f1, to 0,1 bit in spreading code Corresponding normalization instantaneous frequency adds up, and the calculation formula for the sum that added up is as follows:
Wherein, P is over-sampling multiple.
8. the FASST signal recognition method according to claim 7 based on instantaneous frequency, which is characterized in that in step 4) Normalize the zero-mean frequency absolute value of the difference of the cumulative sum of instantaneous frequency are as follows:
Df (n)=| sf0(n)-fmean(n)|
Wherein, fmean(n)=[sf0(n)+sf1(n)]/2。
9. the FASST signal recognition method according to claim 8 based on instantaneous frequency, which is characterized in that every symbol takes 1 The df (n) of a sampling point adds up, and the code element number that adds up is M, and the calculation formula for sliding cumulative sum at equal intervals of df (n) can be obtained It is as follows:
10. a kind of FASST signal recognition device based on instantaneous frequency, including memory, processor and it is stored in memory In and the computer program that can run on a processor, which is characterized in that the processor is realized following when executing described program Step:
1) acquisition setting length signal data to be processed, by pretreatment by signal data to be processed be converted to sample rate with The matched complex signal of the character rate of FASST signal;
2) the normalization instantaneous frequency of complex signal is calculated using instantaneous correlation method;
3) according to the spreading code characteristic of FASST signal, by all normalizings of frequency corresponding to 0 and 1 bit in a spreading code Change instantaneous frequency sampling point add up to obtain normalization instantaneous frequency it is cumulative with;
4) cumulative according to the corresponding normalization instantaneous frequency of 0 and 1 bit and obtain the absolute of its zero-mean or 1 means frequency difference Value, and judge whether the peak feature of the absolute value meets the first setting peak value condition, if satisfied, being then identified as FASST signal.
11. the FASST signal recognition device according to claim 10 based on instantaneous frequency, which is characterized in that step 4) In obtain absolute value after, also calculate the absolute value sliding at equal intervals it is cumulative and, and judge that this slide the peak for the sum that adds up at equal intervals Whether value meets the second setting peak value condition, if satisfied, being then identified as FASST signal.
12. the FASST signal recognition device according to claim 10 based on instantaneous frequency, which is characterized in that described One to set peak value condition be peak value size between 0.5 overtones band interval and doubled frequency interval, and there are between continuous 16 It is divided into the peak value of spread code length.
13. the FASST signal recognition device according to claim 11 based on instantaneous frequency, which is characterized in that described Two to set peak value condition be peak value size between M/2 overtones band interval and 2M overtones band interval, and there are between 16 continuous It is divided into the peak value of spread code length, wherein M is cumulative code element number.
14. the FASST signal recognition device described in 0,11,12 or 13 based on instantaneous frequency, feature exist according to claim 1 In the pre-treatment step is as follows:
(1) signal data to be processed is transformed to by zero intermediate frequency complex signal by frequency-conversion processing and filtering processing;
(2) sample rate is obtained according to the character rate of FASST signal, signal to be processed is subjected to resampling processing and is converted to letter in reply Number.
15. the FASST signal recognition device according to claim 14 based on instantaneous frequency, which is characterized in that described multiple The instantaneous auto-correlation expression formula of signal are as follows: R (n, m)=s*(n) s (n+m)=A2exp(j2πfiM), wherein A be signal amplitude, fiFor carrier frequency, m is delay interval, and m > 0, is extracted by instantaneous correlation method, calculation formula is as follows:
F in formulasFor the sample frequency of signal, it is as follows that normalization instantaneous frequency is obtained as m=1:
finst(n)=finst(n,1)/fs
16. the FASST signal recognition device according to claim 15 based on instantaneous frequency, which is characterized in that FASST letter Number spreading code be b0=[00011101101], b1=[11100010010], the 1 to 3rd bit, the 7th bit and in spreading code 10 bits correspond to instantaneous frequency f0, the 4 to 6th bit, the 8th bit, the 11st bit correspond to instantaneous frequency f1, to 0,1 ratio in spreading code Normalization instantaneous frequency corresponding to spy adds up, and the calculation formula for the sum that added up is as follows:
Wherein, P is over-sampling multiple.
17. the FASST signal recognition device according to claim 16 based on instantaneous frequency, which is characterized in that step 4) The zero-mean frequency absolute value of the difference of the middle cumulative sum of normalization instantaneous frequency are as follows:
Df (n)=| sf0(n)-fmean(n)|
Wherein, fmean(n)=[sf0(n)+sf1(n)]/2。
18. the FASST signal recognition device according to claim 17 based on instantaneous frequency, which is characterized in that every symbol The df (n) of 1 sampling point is taken to add up, the code element number that adds up is M, and the calculating for sliding cumulative sum at equal intervals of df (n) can be obtained Formula is as follows:
CN201810798961.XA 2018-07-19 2018-07-19 A kind of FASST signal recognition method and device based on instantaneous frequency Active CN108832964B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810798961.XA CN108832964B (en) 2018-07-19 2018-07-19 A kind of FASST signal recognition method and device based on instantaneous frequency

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810798961.XA CN108832964B (en) 2018-07-19 2018-07-19 A kind of FASST signal recognition method and device based on instantaneous frequency

Publications (2)

Publication Number Publication Date
CN108832964A CN108832964A (en) 2018-11-16
CN108832964B true CN108832964B (en) 2019-09-13

Family

ID=64139358

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810798961.XA Active CN108832964B (en) 2018-07-19 2018-07-19 A kind of FASST signal recognition method and device based on instantaneous frequency

Country Status (1)

Country Link
CN (1) CN108832964B (en)

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8363744B2 (en) * 2001-06-10 2013-01-29 Aloft Media, Llc Method and system for robust, secure, and high-efficiency voice and packet transmission over ad-hoc, mesh, and MIMO communication networks
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
CN107490722A (en) * 2017-08-18 2017-12-19 南开大学 A kind of frequency estimating methods of low signal-to-noise ratio real signal

Also Published As

Publication number Publication date
CN108832964A (en) 2018-11-16

Similar Documents

Publication Publication Date Title
US8477750B2 (en) Classification of wireless LAN signals
CN101944961B (en) Double threshold cooperative sensing method in cognitive wireless network
CN105678273B (en) The starting point detection algorithm of radio-frequency fingerprint identification technology transient signal
CN106896407B (en) A kind of microseism signal first break pickup method based on approximate negentropy
CN102332933A (en) Short-term burst spread spectrum signal transmitting and receiving method
CN105071830B (en) A kind of detection recognition method of direct sequence signal
CN101951356B (en) Synchronization method of orthogonal frequency division multiplexing-ultra wideband (OFDM-UWB) system based on peak detection
CN106998586B (en) The synchronization acquiring method of wireless communication system in a kind of high dynamic environment
CN101662305B (en) Pseudo-random code estimation method of direct sequence spread spectrum system
CN101295999A (en) Detection method for accidental precursor access
CN101436877B (en) Method for capturing multi-path interference resistant PN code self-adapting threshold
CN105429719A (en) Strong interference signal detection method based on power spectrum and multiple dimensioned wavelet transformation analysis
CN101895380B (en) Blind estimation bit synchronization method for differential chaotic modulation communication system
CN108366032A (en) A kind of broad sense frequency division multiplexing time-frequency synchronization method for correcting big frequency deviation
CN103888389A (en) Method for estimating amplitude of time-frequency overlapped signals
CN110249542A (en) Digital radio
CN102438334A (en) Method for carrying out modulation recognition through distributed cooperation of multiple sensor nodes
CN105871530B (en) A kind of timing tracking method of anti-high dynamic frequency deviation variation
CN108832964B (en) A kind of FASST signal recognition method and device based on instantaneous frequency
CN109067676B (en) High-precision time domain performance evaluation method for satellite navigation signals
CN109104215A (en) A kind of Frequency Hopping Signal chip rate blind estimating method based on wavelet transformation
CN108900445A (en) A kind of method and device of signal code rate estimation
US10153804B2 (en) Clear channel assessment
CN105072075A (en) Multi-threshold decision OFDM synchronization method
CN105656511B (en) Differential correlation acquisition method suitable for environment with frequency offset and low signal-to-noise ratio

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant