CN105656511B - Differential correlation acquisition method suitable for environment with frequency offset and low signal-to-noise ratio - Google Patents

Differential correlation acquisition method suitable for environment with frequency offset and low signal-to-noise ratio Download PDF

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CN105656511B
CN105656511B CN201610038307.XA CN201610038307A CN105656511B CN 105656511 B CN105656511 B CN 105656511B CN 201610038307 A CN201610038307 A CN 201610038307A CN 105656511 B CN105656511 B CN 105656511B
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noise ratio
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frequency offset
peak value
low signal
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叶晓青
罗炬锋
邱云周
刘衍青
尚素绢
汪涵
王康如
郑春雷
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Shanghai Internet Of Things Co ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/69—Spread spectrum techniques
    • H04B1/707—Spread spectrum techniques using direct sequence modulation
    • H04B1/7073—Synchronisation aspects
    • H04B1/7075—Synchronisation aspects with code phase acquisition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/69—Spread spectrum techniques
    • H04B1/707—Spread spectrum techniques using direct sequence modulation
    • H04B1/709—Correlator structure

Abstract

The invention relates to a capturing method using unbiased differential correlation and coherent accumulation, which is suitable for environments with frequency deviation and low signal-to-noise ratio, and comprises the following steps: segmenting the received signal according to the code length period, and correlating the sequence obtained after segmentation with the corresponding local code word to eliminate the pseudo code information; performing M-order unbiased differential correlation on the sequence without the pseudo code information to improve the signal-to-noise ratio of the sequence; performing coherent accumulation on the result after the M-order correlation operation to obtain a peak value; and comparing the peak value with the adaptive threshold, adding one time of confirmation after the peak value exceeds the adaptive threshold, and performing correct capture if the peak value still exceeds the threshold. The invention can improve the capture performance under low signal-to-noise ratio.

Description

Differential correlation acquisition method suitable for environment with frequency offset and low signal-to-noise ratio
Technical Field
The invention relates to the technical field of wireless communication, in particular to a capturing method utilizing unbiased differential correlation and coherent accumulation, which is suitable for environments with frequency deviation and low signal-to-noise ratio.
Background
Acquisition is a key technical problem in the research of the field of wireless communication, and the performance of acquisition determines the performance of the system to a great extent. Meanwhile, in view of low cost, a common crystal oscillator is generally selected, and the receiving and transmitting frequency deviation can reach 40 PPM. For conventional correlation acquisition, the existence of frequency offset can cause serious attenuation to a correlation peak value, and the acquisition performance is deteriorated. Therefore, an acquisition algorithm for a low signal-to-noise ratio environment with frequency offset becomes an indispensable key technology of a wireless communication system.
For the capture algorithm with frequency offset, certain research results are available at home and abroad. The traditional differential capture is simple to realize and can eliminate the influence of frequency offset, but with the increase of PN codes and the reduction of signal-to-noise ratio, the capture sensitivity lost by adopting differential processing is too much. The performance of the capturing algorithm based on the FFT is related to the number of points of the FFT, the cost of resources is overlarge under the condition of low signal to noise ratio, and a fence effect exists, so that the capturing performance is greatly influenced. The two-dimensional search and acquisition algorithm adopting pseudo code synchronization and frequency offset estimation is generally used for weak GPS signals, has long acquisition time and is not suitable for DSSS application scenes under low signal-to-noise ratio.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a differential correlation acquisition method suitable for the environment with frequency offset and low signal-to-noise ratio so as to improve the acquisition performance under the low signal-to-noise ratio.
The inventor finds that the Direct Sequence Spread Spectrum (DSSS) communication technology adopts the pseudo-random code as a basic signal for spread spectrum modulation, has the characteristics of strong anti-interference capability, low transmitting power, low interception rate, good confidentiality and the like, and is commonly used in the application environment with low signal-to-noise ratio. The low signal-to-noise ratio can cause great deterioration to the correlation peak of the traditional acquisition algorithm, and the acquisition performance of the DSSS communication system under the low signal-to-noise ratio needs to be considered for the synchronization problem.
The technical scheme adopted by the invention for solving the technical problems is as follows: the differential correlation acquisition method is suitable for the environment with frequency deviation and low signal-to-noise ratio, and comprises the following steps:
(1) segmenting a received signal according to integral multiple of code length, matching and correlating a sequence obtained after segmentation with a corresponding local code word, and eliminating pseudo code information when code chips are synchronous;
(2) performing M-order unbiased differential correlation on the sequence without the pseudo code information to improve the signal-to-noise ratio of the sequence;
(3) performing coherent accumulation on the result after the M-order correlation operation to obtain a peak value;
(4) comparing the peak value with a self-adaptive threshold, entering the step (5) when the peak value exceeds the self-adaptive threshold, and returning to the step (1) after adjusting the phase otherwise;
(5) and confirming after N (N is the code length) chips, judging whether the current peak value still exceeds the adaptive threshold, if so, determining to acquire correctly, otherwise, returning to the step (1) after adjusting the phase.
The received signal in the step (1) is
Figure GDA0002313439830000021
Where a (k) represents the pseudo-code signal, Δ ω is the frequency offset, θ is the local phase, n (k) is the mean zero, and the variance σ is2White Gaussian noise of (P)sRepresenting sampling point power, T representing sampling period, and k representing discretization sampling point label; the sequence after eliminating the pseudo code information is
Figure GDA0002313439830000022
Wherein | a (k) cells do not21, x (k) represents a signal component.
The setting of M in step (2) is determined according to the maximum frequency offset existing in the system, so as to ensure that the phase change related to each order does not cause obvious attenuation of the peak value, and therefore, the requirement of meeting the requirement is met
Figure GDA0002313439830000023
Where Δ ω is the frequency offset, TcRepresenting the chip period.
The step (2) performs M-order unbiased correlation on the sequence with the pseudo code information removed to obtain M correlation values as follows:
Figure GDA0002313439830000024
wherein x isiTo remove the received signal of the pseudo code, N represents the spreading code length.
The coherent accumulation calculation of the step (3) is as follows:
Figure GDA0002313439830000025
the peak value obtained is
Figure GDA0002313439830000026
The selection mode of the self-adaptive threshold in the step (4) is as follows: and calculating the average power of the background noise of the received signal in the window, multiplying the obtained average power by a fixed coefficient, comparing the multiplied average power with a fixed threshold, and taking the larger value between the obtained average power and the fixed threshold as an adaptive threshold.
Advantageous effects
Due to the adoption of the technical scheme, compared with the prior art, the invention has the following advantages and positive effects: when the correlation peak is calculated, M-order unbiased differential correlation and coherent accumulation are firstly carried out on the signal, so that the signal-to-noise ratio of the signal can be improved, and the capturing can ensure higher detection probability under the environment with very low signal-to-noise ratio. In order to reduce false alarm probability, the invention selects to add a confirmation step after capturing the signal exceeding the threshold, namely, judging whether the related peak value still exceeds the threshold once again at an interval of a pseudo code period so as to ensure the capturing performance under the environment with extremely low signal to noise ratio.
Drawings
FIG. 1 is a flow chart of the present invention;
fig. 2 is a graph of the acquisition performance of the present invention.
Detailed Description
The invention will be further illustrated with reference to the following specific examples. It should be understood that these examples are for illustrative purposes only and are not intended to limit the scope of the present invention. Further, it should be understood that various changes or modifications of the present invention may be made by those skilled in the art after reading the teaching of the present invention, and such equivalents may fall within the scope of the present invention as defined in the appended claims.
The present invention provides an acquisition method adapted to the environment with frequency offset and low signal-to-noise ratio, and a specific embodiment in DSSS system communication will be described in detail with reference to the accompanying drawings, as shown in fig. 1.
In the DSSS communication system, O-QPSK modulation is adopted, and the sampling signal with carrier frequency offset at the receiving end is as follows:
Figure GDA0002313439830000031
where a (k) is a pseudo code signal with a code length N, Δ ω is a frequency offset, T is a sampling period, and k represents a discretized sampling point index. θ is the initial phase mismatch, n (k) is white gaussian noise, and Ps represents the power of the sample point.
Multiplying the received signal by local pseudo code, if it is correct synchronous point, eliminating pseudo code information, the sequence after eliminating pseudo code information is
Figure GDA0002313439830000032
Wherein | a (k) messaging21, x (k) represents a signal component. At this time, t (k) has removed the pseudo-code information, but the noise interference is still large at low snr. Unbiased differential correlation of order M is performed on t (k),
the specific calculation of the unbiased differential correlation of order M (considering only the signal) for each segment (P ═ 1, 2.. P) is:
Figure GDA0002313439830000041
Figure GDA0002313439830000042
Figure GDA0002313439830000043
...
Figure GDA0002313439830000044
obtaining a correlation value:
Figure GDA0002313439830000045
the specific calculation of coherent accumulation is
R(1)＝Rp＝1(1)+Rp＝2(1)+...+Rp＝P(1)
R(2)＝Rp＝1(2)+Rp＝2(2)+...+Rp＝P(2)
...
R(M)＝Rp＝1(M)+Rp＝2(M)+...+Rp＝P(M)
Order to
R(m)＝R1(m)+R2(m)+R3(m)+R4(m) (4)
Wherein
Figure GDA0002313439830000046
R1Is a useful signal term, and R2，R3，R4Is the noise term. Since the noise mean is 0, R is known easily2，R3，R4The mean value is also 0.
Separately determining the signal and noise powers of
Figure GDA0002313439830000051
Where Δ f represents the frequency offset.
For multiplication of signal and noise, there are
Figure GDA0002313439830000052
From the nature of white gaussian noise, the above formula is not zero only when k is l, and can be obtained
Figure GDA0002313439830000053
The same can be obtained
Figure GDA0002313439830000054
Where σ represents the variance.
The fourth term is a noise multiplication term, having
Figure GDA0002313439830000055
The noise average power after correlation is
Figure GDA0002313439830000056
Signal to noise ratio of the original signal of
Figure GDA0002313439830000057
The signal-to-noise ratio after correlation processing and coherent accumulation is
Figure GDA0002313439830000058
It can be seen that when N is larger, the signal-to-noise ratio after processing is improved more obviously than before. M is the correlation order and is set according to the maximum frequency offset existing in the system, so that the phase change between R (1), R (M) does not cause obvious peak attenuation.
The correlation peak obtained after coherent accumulation is:
Figure GDA0002313439830000061
m is the order of the unbiased differential correlation, and the setting of M is determined according to the maximum frequency offset existing in the system, so as to ensure that the phase change of the correlation of each order does not cause obvious attenuation of the peak value, and therefore, the requirement of meeting the requirement is met
Figure GDA0002313439830000062
Wherein, TcRepresenting the chip period. In this embodiment, M is 30, and it can be ensured that the correlation peak is still obvious at the maximum frequency offset.
And after coherent accumulation, obtaining a peak value, and comparing and judging the peak value with a self-adaptive threshold. The selection mode of the self-adaptive threshold is as follows: and calculating the average power of the background noise of the received signal in the window, multiplying the obtained average power by a fixed coefficient, comparing the multiplied average power with a fixed threshold, and taking the larger value between the obtained average power and the fixed threshold as an adaptive threshold.
In order to reduce the false alarm probability, a confirmation step can be selected to be added after the acquisition exceeds the threshold, namely, whether the correlation peak value still exceeds the threshold is judged once again at an interval of a pseudo code period so as to ensure the acquisition performance under the environment with extremely low signal to noise ratio.
FIG. 2 is a graph of the performance of the acquisition of the present invention, comparing the conventional difference and the difference uncorrelated method, and using the probability of correct acquisition as the evaluation criterion.
The invention aims to solve the capture problem of a long code word spread spectrum system, the method groups the received signals according to integral multiple of the code length, each group is correlated with a corresponding local pseudo code, and the influence of pseudo code information can be eliminated when the code chips are synchronous; secondly, carrying out M-order non-deviation phase correlation on the sequence with the pseudo code information eliminated to obtain M correlation values; and then, carrying out coherent accumulation on the processed sequence, and further improving the signal-to-noise ratio of the sequence. And comparing and judging the accumulated peak value with a self-adaptive threshold, thereby improving the detection probability. Therefore, compared with the traditional differential acquisition algorithm, the method has better acquisition performance under the condition of low signal-to-noise ratio. The method can be applied to the fields of ultra-long code words, ultra-low signal-to-noise ratio and long-distance communication application.

Claims (4)

1. A differential correlation acquisition method suitable for the environment with frequency deviation and low signal-to-noise ratio is characterized by comprising the following steps:
(1) the received signal is segmented according to integral multiple of the code length, the sequence obtained after segmentation is matched and correlated with the corresponding local code word, and the pseudo code information is eliminated when the code chips are synchronous;
(2) performing M-order unbiased differential correlation on the sequence without the pseudo code information to improve the signal-to-noise ratio of the sequence, wherein the setting of M is determined according to the maximum frequency offset existing in the system;
(3) performing coherent accumulation on the result after the M-order correlation operation to obtain a peak value;
(4) comparing the peak value with a self-adaptive threshold, entering the step (5) when the peak value exceeds the self-adaptive threshold, and returning to the step (1) after adjusting the phase otherwise;
(5) and confirming after N chips are spaced, judging whether the current peak value still exceeds a self-adaptive threshold, if so, determining to acquire correctly, otherwise, returning to the step (1) after the phase is adjusted, wherein N is the code length.
2. The differential correlation acquisition method adapted to the environment with frequency offset and low signal-to-noise ratio of claim 1, wherein the received signal in step (1) is
Figure FDA0002313439820000011
Where a (k) represents the pseudo-code signal, Δ ω is the frequency offset, θ is the local phase, n (k) is the mean zero, and the variance σ is2White Gaussian noise of (P)sRepresenting sampling point power, T representing sampling period, and k representing discretization sampling point label; the sequence after eliminating the pseudo code information is
Figure FDA0002313439820000012
Wherein | a (k) cells do not21, x (k) represents a signal component.
3. The differential correlation acquisition method adapted to the environment with frequency offset and low signal-to-noise ratio according to claim 1, wherein M in step (2) is 30.
4. The differential correlation acquisition method adapted to the environment with frequency offset and low signal-to-noise ratio according to claim 1, wherein the adaptive threshold in step (4) is selected by: and calculating the average power of the background noise of the received signal in the window, multiplying the obtained average power by a fixed coefficient, comparing the multiplied average power with a fixed threshold, and taking the larger value between the obtained average power and the fixed threshold as an adaptive threshold.
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