CN115643139A - Frequency offset resistant burst signal detection system and detection method - Google Patents
Frequency offset resistant burst signal detection system and detection method Download PDFInfo
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Abstract
The invention discloses a frequency deviation resistant burst signal detection system and a detection method, wherein the detection system comprises a synchronous code baseband waveform generation module, a correlation calculation module, a correlation peak search and judgment module, a burst data caching module, a frequency deviation correction module and a de-modulation module which is respectively connected with the synchronous code baseband waveform generation module and the frequency deviation estimation module, and the frequency deviation estimation module is connected with the frequency deviation correction module. The invention can obtain good burst signal detection performance under the conditions of lower signal-to-noise ratio and larger frequency offset, and is insensitive to the amplitude of the input signal. Meanwhile, the frequency offset can be accurately estimated and corrected, so that the subsequent demodulation performance is ensured.
Description
Technical Field
The invention relates to a detection method of burst signals (such as frequency hopping signals, satellite TDMA signals and the like) in non-cooperative communication, which is mainly used in the field of communication countermeasure and aims at real-time detection of unknown radio signals of enemies to obtain the initial position of the signal burst and provide support for burst signal demodulation.
Background
In the satellite TDMA system communication mode, the key to the demodulation of the received signal is to accurately determine the starting position of each time slot burst and to quickly synchronize the carrier and the code element. Due to the influence of factors such as discontinuity of each burst of received data in time, movement and drift of a satellite, change of a transmission medium, change of transmission delay of equipment along with temperature and the like, a received burst signal changes along with time relative to a nominal position, synchronization information obtained from a previous burst cannot be used by a next burst, and each burst of a receiving end is required to achieve carrier synchronization and symbol synchronization and be stable within a short time at the beginning of each burst of the receiving end. In cooperative communication, both parties to a TDMA system communication employ agreed carrier recovery/symbol timing sequences. For non-cooperative communication, when the agreed carrier synchronization/symbol timing sequence is unknown, not only is it difficult to achieve fast carrier synchronization and symbol synchronization, but also it is difficult to accurately detect the starting position of the signal burst.
Similarly, in a frequency hopping communication system, the burst data segment received at each frequency hopping point is also discontinuous in time, and for non-cooperative communication, the frequency hopping sequence and the frequency hopping pattern are unknown, and in order to correctly demodulate the information contained in the burst signal, it is first necessary to perform start position detection and frequency offset estimation for each burst signal.
Therefore, in non-cooperative communication, in order to correctly receive and demodulate each burst signal for all burst communication systems, it is necessary to correctly detect the start position of each burst signal and accurately estimate the frequency of the signal.
The burst signal detection method mainly includes an energy detection method, a correlation detection method, and the like. The energy detection method is simple in calculation and small in calculation amount, but the anti-interference capability is poor. The relevant detection method has stronger anti-interference capability, but is more sensitive to frequency deviation, and particularly for MSK signals, the frequency modulation index is the theoretical minimum value and is more sensitive to frequency deviation.
The communication technology, vol.45, no.06,2012, provides a TDMA signal blind detection algorithm based on double sliding windows, which belongs to an energy detection algorithm, has the characteristics of small operand and strong real-time performance, has better effect under the condition that the input signal-to-noise ratio is greater than 10dBm, but the detection result is rapidly deteriorated under the condition that the input signal-to-noise ratio is poor. Other energy detection methods (Yao Guoyi, li Xin, lanreota, a burst communication signal detection and frequency offset estimation algorithm, a communication system and network technology, vol.40no.4 2014) have similar defects and poor interference resistance, and can be used only in an environment with good signal quality.
Du Qian, a practical MPSK/TDMA burst blind demodulation scheme, radio engineering, vol.46, no.3,2016, proposes a correlation detection algorithm based on unique words, which describes the burst detection principle but does not describe how to set the correlation peak decision threshold when the input signal amplitude fluctuates greatly. And the influence of frequency deviation is not considered, and the detection effect is poor when the frequency deviation of the received signal is larger. Study on blind communication signal detection technology, liberation force information engineering university, 2016:15-20, the algorithm utilizes the autocorrelation characteristic of the signal, and can carry out blind detection on the signal without any prior information, but the algorithm has the condition that the missed detection probability and the false detection probability are contradictory, so as to avoid missed detection, a larger false detection probability is often caused, namely, the noise is easily mistakenly judged as a useful signal, and the condition is more prominent particularly when the signal quality of the observed data is poor and the signal-to-noise ratio is low.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, provides a frequency deviation resistant burst signal detection system which can obtain good burst signal detection performance under the conditions of lower signal-to-noise ratio and larger frequency deviation, is insensitive to the amplitude of an input signal and can accurately estimate and correct frequency deviation, and provides a corresponding burst signal detection method.
The purpose of the invention is realized by the following technical scheme: a frequency deviation resistant burst signal detection system comprises a synchronous code baseband waveform generation module, a correlation calculation module, a correlation peak search and judgment module, a burst data cache module, a frequency deviation correction module and a de-modulation module which is respectively connected with the synchronous code baseband waveform generation module and the frequency deviation estimation module, wherein the synchronous code baseband waveform generation module, the correlation calculation module, the correlation peak search and judgment module, the burst data cache module and the frequency deviation correction module are sequentially connected, and the frequency deviation estimation module is connected with the frequency deviation correction module.
Further, the synchronization code baseband waveform generating module is configured to perform baseband modulation on the synchronization code UW sequence to obtain a new IQ sequence IQ UW ；
Correlation computation module uses IQ UW Performing sliding correlation operation with a received signal baseband IQ sequence;
the correlation peak searching and judging module is used for performing symbolization processing on the calculation result of the correlation calculation module, searching a correlation peak, comparing the correlation peak with a threshold value, confirming the initial position of a signal, and sending a burst signal to the cache module from the initial position;
the burst data Buffer module is used for storing burst signal baseband IQ data with a certain length into a Buffer according to the duration of the burst signal;
the demodulation module is used for intercepting complex multiplication of a section of burst signal baseband IQ waveform and synchronous code waveform conjugate, solving FFT (fast Fourier transform) through a sequence after complex multiplication, then solving an amplitude spectrum and finding out a position spectral line of the maximum value of the amplitude spectrum;
the frequency offset estimation module is used for accurately estimating the signal frequency offset by adopting a phase difference correction method and outputting a frequency control word;
the frequency deviation correction module is used for carrying out frequency deviation correction on the IQ data in the burst data cache module by using the frequency control word output by the frequency deviation estimation module and outputting a corrected burst IQ stream; thereby completing burst detection and frequency offset correction of the signal.
Another object of the present invention is to provide a method for detecting a burst signal against frequency offset, which comprises the following steps:
s1, generating baseband IQ data: assuming that the sampling rate of the ADC is 93.333MHz and the symbol rate of the transmission signal is 70Kbps, sampling the ADC signal, then carrying out down-conversion to zero frequency through DDC, and then obtaining baseband IQ data after passing through a CIC extraction filter, an FIR filter and resampling;
s2, generating a synchronous code baseband waveform sequence: baseband modulating the UW sequence to generate synchronous code baseband IQ sequence IQ UW ；
S3, generating the synchronous code baseband IQ sequence IQ generated by the synchronous code baseband waveform generating module UW Sending the IQ sequence and the original baseband IQ sequence to a correlation calculation module for correlation calculation to obtain a correlation sequence;
the correlation operation adopts four-term multiplication and convolution as shown in the following formula:
IQ n+i-1 representing the n + i-1 th value of the sequence IQ, IQ u i w Representing IQ uw Sequence ith value, conj () represents the conjugate;
s4, carrying out normalization processing on the correlation value and judging the correlation peak: in a correlation peak searching and judging module, performing symbolization processing on the result of each product, namely taking 1 as a positive number, taking 0 as a negative number-1,0, and then accumulating; rewriting formula (1) to the form of formula (2):
real (core (n)) refers to the real part of core (n), imag (core (n)) refers to the imaginary part of core (n), sign () is a sign function;
the correlation peak searching and judging module finds the position where the modulus of the corre (n) exceeds a preset threshold value, namely the starting position of the burst signal, and stably intercepts the burst signal segment from the starting position;
s5, burst data caching: the correlation peak searching and judging module outputs the intercepted burst signal segment to a burst data caching module for caching, and the caching length is determined by the duration of the burst signal;
s6, frequency offset estimation is carried out: in the demodulation module, the demodulation calculation is carried out on the signal according to the formula (3):
namely complex multiplication of an input baseband IQ sequence and a conjugate of a synchronous code baseband IQ sequence, and then accurately estimating frequency offset by using a phase difference correction method;
the frequency offset estimation module divides the 256-point complex multiplication result in the demodulation module into two groups, namely 1 to 128 are a first group, and 129 to 256 are a second group; the two groups are respectively subjected to FFT, then the amplitude spectrums of the two groups are obtained, the maximum positions k1 and k2 of the two groups of amplitude spectrum results are found, taking any one of k1 and k2 as a label k; two groups of IQ data with 256 points and the mark numbers of k and k +128 are taken, phase angles are calculated, and then phase angle differences are calculated; and (3) carrying out normalization processing on the phase angle difference: dividing by 2 pi to obtain a decimal delta with the value range of [ -0.5,0.5];
the calculation of the obtained frequency offset is shown in formula (4):
Δf＝(k-δ)*f s /N (4)
in the formula, k is the maximum position of a spectral line and is obtained through a frequency spectrum; f. of s Is the sampling rate, N is the length of FFT;
converting equation (4) into a frequency control word generating equation, as shown in (5):
pinc＝(k-δ)*2 32 /128 (5)
ping is the frequency control word of the input DDS;
s7, frequency offset correction is carried out: the frequency offset correction module uses the frequency control word of the frequency offset estimation module to generate a carrier wave and carries out frequency offset correction on the cache data point in the burst data cache module; the frequency offset correction module uses a complex multiplier to carry out operation, and the specific operation method is shown as the following formula:
SampleCorrectSeq(n)＝SampleSeq(n)*e j2πΔfn ，n＝1,2,3,…,M (6)
SampleSeq (n) indicates the value of the nth data of the burst signal before frequency offset correction, sampleCorrectSeq (n) indicates the value of the nth data of the burst signal after frequency offset correction, M indicates the number of buffered burst data points, e jwn The result of complex multiplication is the burst IQ flow after frequency deviation correction, and then output to the back end for demodulation processing.
The invention can obtain good burst signal detection performance under the conditions of lower signal-to-noise ratio and larger frequency offset, and is insensitive to the amplitude of the input signal. Meanwhile, the frequency offset can be accurately estimated and corrected, so that the subsequent demodulation performance is ensured. The concrete advantages are shown in the following aspects:
1. the correlation detection algorithm used by the invention has good performance under low signal-to-noise ratio, when E b /N 0 When the signal intensity is more than 5dB, the detection accuracy reaches 100%, and compared with other detection methods, the performance is obviously improved, so that the method has important significance for detecting signals in the environment with low signal to noise ratio.
2. The correlation detection algorithm used by the invention carries out convolution operation four-term multiplication accumulation on the IQ sequence obtained by modulating the baseband IQ sequence and the UW sequence baseband. The method has good anti-noise and anti-frequency deviation capabilities when applied to burst detection, the frequency deviation can reach 50% of the code element rate, and compared with the common related detection, the method is weaker in anti-frequency deviation capability (less than 10% of the code element rate), and the anti-frequency deviation capability is obviously improved.
3. Due to the fast movement of the monitored object, the received signal amplitude fluctuates greatly, and the signal processing in the device is usually affected greatly. The method for symbolizing the correlation value adopted in the invention has no influence on correct detection when the amplitude of the input signal fluctuates greatly, namely the method is insensitive to the amplitude fluctuation of the input signal.
4. The method not only can accurately detect the signal, but also can accurately estimate the frequency deviation generated in the transmission process of the signal, and the precision can reach the Hz level. And then, the frequency of the received signal is corrected by utilizing the estimated frequency offset value, so that the demodulation performance of the signal can be greatly improved.
Drawings
FIG. 1 is a schematic diagram of a system for detecting a burst signal with frequency offset resistance according to the present invention;
FIG. 2 is a correlation calculation result of a conventional algorithm at a symbol rate of 5% frequency offset;
fig. 3 is a correlation calculation result of the algorithm of the present invention at a symbol rate of 5% frequency offset.
Detailed Description
As shown in fig. 1, the system for detecting a burst signal with frequency offset resistance of the present invention includes a synchronous code baseband waveform generating module UwSeqGen, a correlation calculating module CorreCal, a correlation peak searching and deciding module FindPeaks, a burst data buffering module BurstDataBuf and a frequency offset correcting module FreqErrCorrect, which are connected in sequence, and a de-modulating module Cmpy respectively connected to the synchronous code baseband waveform generating module and the frequency offset estimating module FreqErrCal, and the frequency offset estimating module is connected to the frequency offset correcting module.
The synchronous code baseband waveform generating module is used for generating a UW sequence of the synchronous codeThe new IQ sequence IQ is obtained by baseband modulation of the column UW ；
Correlation calculation module is used for IQ of sequence UW Performing sliding correlation operation with a received signal baseband IQ sequence, and outputting a correlation calculation result value;
the correlation peak searching and judging module is used for performing symbolization processing on the calculation result of the correlation calculation module, searching a correlation peak, comparing the correlation peak with a threshold value, confirming the initial position of a signal, and sending a burst signal to the cache module from the initial position;
the burst data Buffer module is used for storing burst signal baseband IQ data with a certain length into a Buffer according to the duration of the burst signal;
the demodulation module is used for intercepting complex multiplication of a section of burst signal baseband IQ waveform and synchronous code waveform conjugate, solving FFT (fast Fourier transform) through a sequence after complex multiplication, then solving an amplitude spectrum and finding out a position spectral line of the maximum value of the amplitude spectrum;
the frequency offset estimation module is used for accurately estimating the signal frequency offset by adopting a phase difference correction method and outputting a frequency control word;
the frequency deviation correction module is used for carrying out frequency deviation correction on the IQ data in the burst data cache module by using the frequency control word output by the frequency deviation estimation module and outputting a corrected burst IQ stream; thereby completing burst detection and frequency offset correction of the signal.
Another object of the present invention is to provide a method for detecting a burst signal against frequency offset, which comprises the following steps:
s1, generating baseband IQ data: assuming that the sampling rate of the ADC is 93.333MHz and the symbol rate of the transmission signal is 70Kbps, sampling the ADC signal, then performing down-conversion to zero frequency through DDC, and then performing decimation by a CIC decimation filter (160 times decimation), an FIR filter and resampling to obtain a zero-frequency signal with 4 times of symbol rate, namely baseband IQ data;
s2, generating a synchronous code baseband waveform sequence: in S1, the resampling rate is 4 times the symbol rate, and there are 4 sampling points per symbol. UwSeqGen carries out baseband modulation on 64 input synchronous code UW sequences to generate a synchronous code baseband IQ sequence IQ with the length of 256 UW ；
S3, generating synchronous code baseband IQ sequence IQ generated by a synchronous code baseband waveform generating module UW Sending the IQ sequence and the original baseband IQ sequence to a correlation calculation module for correlation calculation (convolution calculation) to obtain a correlation sequence;
the conventional correlation operation is calculated by using formula (a), i.e. conjugate and reverse sequence are taken for the sequence generated by UwSeqGen, and then the product and the addition are performed with the resample sequence.
However, in practical applications, because the accurate frequency point value and the influence of factors such as an asynchronous clock system and doppler are unknown, the frequency control word set by the DDC down converter is usually biased, and a signal after DDC is not a zero-frequency baseband in a strict sense but has a frequency offset, which may reduce subsequent signal demodulation performance. Fig. 2 shows the correlation result when there is a frequency difference of 5% of the symbol rate, and there is no obvious correlation peak inside, i.e. the starting position of the signal cannot be found. It can be seen that the correlation calculation using equation (a) is very tolerant to signal frequency offset.
The invention improves the formula (a), and the correlation operation adopts four-term multiplication-addition convolution as shown in the following formula:
IQ n+i-1 representing the n + i-1 th value of the sequence IQ,
representing IQ uw Sequence ith value, conj () represents the conjugate; n has no upper limit, and sliding calculation is always carried out to finally obtain a discrete corre (n) sequence; equation (1) can be viewed as the multiplication of products of two sets of conjugate multiplications, the first set being indexed from 1 to 252 and the second set being indexed from 5 to 256. Equation (1) in the ideal case of no noise, the frequency offset may even exceed 50% of the symbol rate. By the sameThe result shown in fig. 3 can be obtained by testing the symbol rate 5% frequency offset, and the correlation peak is very obvious as can be seen from the figure.
As can be seen from fig. 3, once a proper threshold value is set, the peak of the correlation value can be found, and the start position of the signal is obtained: and when the correlation value calculated in real time reaches the peak value, judging the correlation value as the initial position of the signal.
There is also a barrier to the practical signal processing using equation (1), i.e. the threshold is difficult to set, and needs to be adjusted according to the signal amplitude. I.e. the amplitude of each channel signal may vary and the amplitude of the individual channel signals may also vary over time, which makes the adjustment of the threshold uncontrollable and therefore the sequence of correlation values has to be normalized so that the threshold setting is uniform and invariant.
S4, carrying out normalization processing on the correlation value and judging the correlation peak: equation (1) is an accumulator with four-term multiplication, and the product of each term is affected by the amplitude of the input signal, so that the related peak decision threshold cannot be determined. In order to make the decision threshold not influenced by the input signal amplitude, in the search of relevant peak and decision module, carry on the symbolization processing to the result of each item of products, namely the positive number takes 1, the negative number takes-1,0 and takes 0, then accumulate; as such, regardless of the amplitude of the input signal, the result of the accumulator is normalized to a range between-252 and 252 for either the real or imaginary part; rewriting formula (1) to the form of formula (2):
real (corr (n)) refers to the real part of corr (n), imag (corr (n)) refers to the imaginary part of corr (n), sign () is a sign function;
through actual measurement, the effect of the formula (2) is obvious, even if the amplitude fluctuation of the input signal is large, the correlation value is always larger than 210 when the signals are correlated, and the correlation value does not exceed 100 when the signals are uncorrelated. Taking the threshold as 200, finding the position where the modulus of the core (n) exceeds the preset threshold value by a related peak searching and judging module, namely the starting position of the burst signal, and stably intercepting the burst signal segment from the starting position;
s5, burst data caching: the correlation peak searching and judging module outputs the intercepted burst signal segment to a burst data caching module for caching, and the caching length is determined by the duration of the burst signal; in this embodiment, 2800 sample points are buffered, approximately 700 symbols long. And then, estimating the frequency offset of the sequence, and performing frequency offset correction on the whole data segment to calculate a frequency control word.
S6, frequency offset estimation is carried out: in the demodulation module, the demodulation calculation is carried out on the signal according to the formula (3):
namely, complex multiplication of an input baseband IQ sequence and a conjugate of a synchronous code baseband IQ sequence, and then accurately estimating frequency offset by using a phase difference correction method.
The frequency offset estimation module divides the 256-point complex multiplication result in the demodulation module into two groups, namely 1 to 128 are a first group, and 129 to 256 are a second group; the two groups are respectively subjected to FFT, then the amplitude spectrums of the two groups are obtained, the maximum positions k1 and k2 of the two groups of amplitude spectrum results are found, taking any one of k1 and k2 as a label k; two groups of IQ data with 256 points and the labels of k and k +128 are taken, the phase angles are calculated, and then the phase angle difference is calculated; and (3) carrying out normalization processing on the phase angle difference: dividing by 2 pi to obtain a decimal delta with the value range of [ -0.5,0.5];
the calculation of the obtained frequency offset is shown in formula (4):
Δf＝(k-δ)*f s /N (4)
in the formula, k is the maximum position of a spectral line and is obtained through a frequency spectrum; f. of s Is the sampling rate, N is the length of FFT;
then, in the FPGA, the ipcore of the DDS is used to generate a carrier, corresponding to equation (4), and the frequency control word of the DDS is 32 bits, and equation (4) is converted into a generation equation of the frequency control word, as shown in (5):
pinc＝(k-δ)*2 32 /128 (5)
ping is the frequency control word of the input DDS;
s7, frequency offset correction is carried out: the frequency offset correction module uses the frequency control word of the frequency offset estimation module to generate a carrier wave and carries out frequency offset correction on the cache data point in the burst data cache module; the frequency offset correction module uses a complex multiplier to carry out operation, and the specific operation method is shown as the following formula:
SampleCorrectSeq(n)＝SampleSeq(n)*e j2πΔfn ，n＝1,2,3,…,M (6)
SampleSeq (n) denotes the value of the nth data of the burst signal before frequency offset correction, sampleCorrectSeq (n) denotes the value of the nth data of the burst signal after frequency offset correction, M denotes the number of buffered burst data points, e jwn e j2πΔfn The complex multiplication result is the burst IQ flow corrected by frequency deviation and then output to the back end for demodulation processing.
It will be appreciated by those of ordinary skill in the art that the embodiments described herein are intended to assist the reader in understanding the principles of the invention and are to be construed as being without limitation to such specifically recited embodiments and examples. Those skilled in the art can make various other specific changes and combinations based on the teachings of the present invention without departing from the spirit of the invention, and these changes and combinations are within the scope of the invention.
Claims (3)
1. The system is characterized by comprising a synchronous code baseband waveform generating module, a correlation calculation module, a correlation peak searching and judging module, a burst data caching module, a frequency offset correction module and a de-modulation module, wherein the synchronous code baseband waveform generating module, the correlation calculation module, the correlation peak searching and judging module, the burst data caching module and the frequency offset correction module are connected in sequence, the de-modulation module is respectively connected with the synchronous code baseband waveform generating module and the frequency offset estimation module, and the frequency offset estimation module is connected with the frequency offset correction module.
2. The system according to claim 1, wherein the sync code baseband waveform generating module is configured to perform baseband modulation on the sequence of the sync code UW to obtain a new IQ sequence UW ；
Correlation calculation module for calculating correlation between sequencesIQ UW Performing sliding correlation operation with a received signal baseband IQ sequence;
the correlation peak searching and judging module is used for symbolizing the calculation result of the correlation calculation module, searching a correlation peak, comparing the correlation peak with a threshold value, confirming the initial position of a signal, and sending a burst signal into the cache module from the initial position;
the burst data Buffer module is used for storing burst signal baseband IQ data with a certain length into a Buffer according to the duration of the burst signal;
the demodulation module is used for intercepting complex multiplication of a section of burst signal baseband IQ waveform and synchronous code waveform conjugate, solving FFT (fast Fourier transform) through a sequence after complex multiplication, then solving an amplitude spectrum and finding out a position spectral line of the maximum value of the amplitude spectrum;
the frequency offset estimation module is used for accurately estimating the signal frequency offset by adopting a phase difference correction method and outputting a frequency control word;
the frequency deviation correction module is used for carrying out frequency deviation correction on the IQ data in the burst data cache module by using the frequency control word output by the frequency deviation estimation module and outputting a corrected burst IQ stream; thereby completing burst detection and frequency offset correction of the signal.
3. A burst signal detection method for resisting frequency deviation is characterized by comprising the following steps:
s1, generating baseband IQ data: assuming that the sampling rate of the ADC is 93.333MHz and the symbol rate of the transmission signal is 70Kbps, sampling the ADC signal, then carrying out down-conversion to zero frequency through DDC, and then obtaining baseband IQ data after passing through a CIC extraction filter, an FIR filter and resampling;
s2, generating a synchronous code baseband waveform sequence: baseband modulating the UW sequence to generate synchronous code baseband IQ sequence IQ UW ；
S3, generating synchronous code baseband IQ sequence IQ generated by a synchronous code baseband waveform generating module UW Sending the IQ sequence and the original baseband IQ sequence to a correlation calculation module for correlation calculation to obtain a correlation sequence;
the correlation operation adopts four-term multiplication and convolution as shown in the following formula:
IQ n+i-1 representing the n + i-1 th value of the sequence IQ,
representing IQ uw Sequence ith value, conj () represents the conjugate;
s4, normalization processing and correlation peak judgment of correlation values: in a correlation peak searching and judging module, performing symbolization processing on the result of each product, namely taking 1 as a positive number, taking 0 as a negative number-1,0, and then accumulating; rewriting formula (1) to the form of formula (2):
real (core (n)) refers to the real part of core (n), imag (core (n)) refers to the imaginary part of core (n), sign () is a sign function;
the correlation peak searching and judging module finds the position where the modulus of the corre (n) exceeds a preset threshold value, namely the starting position of the burst signal, and stably intercepts the burst signal segment from the starting position;
s5, burst data caching: the correlation peak searching and judging module outputs the intercepted burst signal segment to a burst data caching module for caching, and the caching length is determined by the duration of the burst signal;
s6, frequency offset estimation is carried out: in the demodulation module, the demodulation calculation is carried out on the signal according to the formula (3):
namely complex multiplication of an input baseband IQ sequence and a conjugate of a synchronous code baseband IQ sequence, and then accurately estimating frequency offset by using a phase difference correction method;
the frequency offset estimation module divides the 256-point complex multiplication result in the demodulation module into two groups, namely 1 to 128 are a first group, and 129 to 256 are a second group; the two groups are respectively subjected to FFT, then the amplitude spectrums of the two groups are obtained, the maximum positions k1 and k2 of the two groups of amplitude spectrum results are found, taking any one of k1 and k2 as a label k; two groups of IQ data with 256 points and the mark numbers of k and k +128 are taken, phase angles are calculated, and then phase angle differences are calculated; and (3) carrying out normalization processing on the phase angle difference: dividing by 2 pi to obtain a decimal delta with the value range of [ -0.5,0.5];
the calculation of the obtained frequency offset is shown as formula (4):
Δf＝(k-δ)*f s /N (4)
in the formula, k is the maximum position of a spectral line and is obtained through a frequency spectrum; f. of s Is the sampling rate, N is the length of FFT;
converting equation (4) into a frequency control word generating equation, as shown in (5):
pinc＝(k-δ)*2 32 /128 (5)
ping is the frequency control word of the input DDS;
s7, frequency offset correction is carried out: the frequency offset correction module uses the frequency control word of the frequency offset estimation module to generate a carrier wave and carries out frequency offset correction on the cache data point in the burst data cache module; the frequency offset correction module uses a complex multiplier to carry out operation, and the specific operation method is shown as the following formula:
SampleCorrectSeq(n)＝SampleSeq(n)*e j2πΔfn ，n＝1,2,3,…,M (6)
SampleSeq (n) denotes the value of the nth data of the burst signal before frequency offset correction, sampleCorrectSeq (n) denotes the value of the nth data of the burst signal after frequency offset correction, M denotes the number of buffered burst data points, e jwn The result of complex multiplication is the burst IQ flow after frequency deviation correction, and then output to the back end for demodulation processing.
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