CN107864032B - Method for fusion processing of bit synchronization and frame synchronization of spread spectrum signal - Google Patents
Method for fusion processing of bit synchronization and frame synchronization of spread spectrum signal Download PDFInfo
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- H04L7/00—Arrangements for synchronising receiver with transmitter
- H04L7/04—Speed or phase control by synchronisation signals
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Abstract
A method for integrating bit synchronization and frame synchronization of spread spectrum signals aims at solving the problems that in the prior art, the frame loss rate is high, the detection error rate is high and the like easily occur in a method of carrying out bit synchronization and frame synchronization by means of a histogram statistics method and a maximum likelihood method, and by means of calculating short code period related energy values, matching filtering calculation data and outputting short code period starting positions at the same time, the problem that signal bit synchronization and frame synchronization cannot be achieved for spread spectrum signals at the same time is solved, stability is good, and reliability is high.
Description
Technical Field
The invention relates to a method for fusion processing of bit synchronization and frame synchronization of spread spectrum signals, belonging to the technical field of communication.
Background
The message communication receiver project requires to receive multiple paths of message communication signals simultaneously, and the receiver can work under the condition of carrier-to-noise ratio C/N034 dB Hz, and the signal capturing and synchronization probability meets the project requirement. The message communication signal format is a short burst mode, and the duration of the signal is variable. The signal is composed of a synchronization header, a service segment and a data segment. The synchronous head is composed of periodic short codes, data modulation is not carried out, the synchronous head is used for a receiver to capture signals, the service section is composed of frame head, user identification and other information, and the data section is communication content. When the message communication receiver captures a signal, the signal synchronization is firstly needed, then the initial position of the communication information is carried out according to the signal synchronization position, then the decoding and the de-framing are carried out, and the content of the message communication is extracted. Therefore, signal synchronization is a very important part of the design of the message receiver.
In the current message communication signal format, the frame identification from the synchronization head to the service segment adopts a periodic spread spectrum short code, and each bit of the frame identification part of the service segment corresponds to two periodic short codes. Before signal synchronization, firstly, the bit synchronization needs to be solved, the initial position of the frame identifier is found, then, the frame synchronization is carried out, and the frame initial position of the message communication signal is found. Thus, the synchronization of the message communication signal includes bit synchronization and frame synchronization.
In the prior art, bit synchronization and improvement are generally performed by using a histogram statistics or maximum likelihood method, but frame synchronization cannot be performed while bit synchronization is performed, and meanwhile, phenomena such as error detection, frame loss and the like are easily caused in the histogram statistics method; by the method of calculating the maximum likelihood, the maximum value position is selected as the initial position in the calculation process of the data energy corresponding to all possible bit edge positions, and the frame loss rate is higher under the condition of weak signal conditions, so that the requirement of the frame synchronization probability is not met.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the method is used for solving the problem that the existing histogram and maximum likelihood method are easy to lose frames and detect errors.
The technical solution of the invention is as follows:
a fusion processing method of spread spectrum signal bit synchronization and frame synchronization comprises the following steps:
(1) dividing a spread spectrum signal to be processed in a digital signal processing channel into N short code periods by taking time T as a time interval, setting a symbol to comprise E short code periods, and setting the length of a frame header to be Q, namely Q symbols;
(2) starting from the first short code period, integrating each symbol to obtain a corresponding symbol correlation value, and demodulating each symbol correlation value to obtain a corresponding symbol correlation value sequence;
(3) starting from the second short code period, integrating each symbol to obtain a corresponding symbol correlation value, and demodulating each symbol correlation value to obtain a corresponding symbol correlation value sequence;
(4) starting from the Xth short code period, integrating each symbol to obtain a corresponding symbol correlation value, and demodulating each symbol correlation value to obtain a corresponding symbol correlation value sequence, wherein the larger the numerical value of X is, the better the fusion effect is;
(5) measuring symbol matched filtering data and related energy value matched filtering data of the currently obtained symbol related value sequence, judging whether the symbol matched filtering data and the related energy value matched filtering data reach a threshold value, if the symbol matched filtering data and the related energy value matched filtering data exceed the threshold value, entering the step (6), and if not, re-performing the step (3) or the step (4);
(6) if the data obtained in the step (5) exceeds the threshold value, judging whether the symbol matching filtering data and the related energy value matching filtering data of the currently obtained symbol related value sequence exceed the threshold value for the first time, if so, performing threshold passing identification on the current short code period and latching the current symbol matching filtering and related energy value matching filtering data value, and if not, entering the step (7);
(7) and (4) if the data obtained in the step (5) is not larger than the threshold value for the first time, comparing the data with the short code period marked in the step (6), if the data is larger than the latched data value in the step (6), canceling the threshold-crossing identifier of the previous short code period, marking the current latched data value and the short code period, and if the data does not exceed the threshold-crossing identifier for the first time in ten continuous measurements, stopping the calculation.
In the step (2), a specific method for obtaining the related symbol value sequence is as follows:
starting from the first short code period, continuously integrating the E short code periods to obtain a first correlation value A1, starting from the E +1 short code period, continuously integrating the E short code periods to obtain a second correlation value A2, and so on, accumulating corresponding one integrated correlation value AQ in each E adjacent short code periods to obtain Q correlation values A1 and A2 … … AQ, and demodulating the Q correlation values to obtain symbols S1 and S2 … … SQ of the Q correlation values.
In the step (3), a specific method for obtaining the related symbol value sequence is as follows:
and continuously integrating the E short code periods from the second short code period to obtain a first correlation value B1, continuously integrating the E short code periods from the E +1 short code period to obtain a second correlation value B2, and repeating the steps, wherein each E adjacent short code periods accumulate corresponding to one integrated correlation value BQ to obtain Q correlation values B1 and B2 … … BQ, and simultaneously demodulating the Q correlation values to obtain symbols Y1 and Y2 … … YQ of the Q correlation values.
In the step (4), a specific method for obtaining the related symbol value sequence is as follows:
starting from the Xth short code period, continuously integrating the E short code periods to obtain a first correlation value X1, starting from the X +1 th short code period, continuously integrating the E short code periods to obtain a second correlation value X2, and so on, accumulating one integrated correlation value XQ corresponding to each E adjacent short code periods to obtain Q correlation values X1 and X2 … … XQ, simultaneously demodulating the Q correlation values to obtain symbols X1 and X2 … … XQ of the Q correlation values, if X is greater than 2, performing the step (4), and if X is 2, not performing the step (4); wherein, the larger X is, the higher the accuracy of the calculation of the symbol matched filter data and the correlation energy value matched filter data is.
In the step (5), symbol matching filtering data measurement is performed on the symbol correlation value sequence obtained in the steps (2), (3) and (4), if the measured data is greater than the symbol matching filtering calculation threshold value, the relevant energy value matching filtering data measurement is performed, if the measured data is greater than the relevant energy value matching filtering calculation threshold value, the step (6) is performed, otherwise, the step (4) is performed again if X is greater than 2; if X is 2, the step (3) is carried out again;
in the step (5), the step of calculating the symbol matching filter data threshold value is:
(a) and (3) calculating the probability of missing detection of symbol matching filtering, wherein the calculation formula is as follows:
in the formula, Pl is the probability of missed detection, PeIn order to receive the error probability of the symbol, s is the length of a frame header sequence to be checked, k is the maximum number of allowed errors during checking, r is an integral variable of a calculus, and the variation range is 0-k;
(b) and calculating the false alarm probability of symbol matching filtering, wherein the calculation formula is as follows:
in the formula, Pf is false alarm probability;
(c) and calculating the symbol matching filtering frame error rate according to the following calculation formula:
P＝Pl+Pf
in the formula, P is the symbol matched filtering frame error rate, i.e. the symbol matched filtering threshold.
In the step (5), the calculation method of the energy matching filtering calculation threshold value Z is that
Z＝P·O
Where O is the average of the accumulated energy in a single symbol.
In the step (6), if the calculated symbol matched filtering calculation data and the calculated related energy value matched filtering calculation data calculated in the step (5) are both greater than the symbol matched filtering calculation threshold value or the calculated related energy value matched filtering calculation threshold value for the first time in the calculation process, the initial position of the current short code period is recorded, the current symbol matched filtering calculation data and the calculated related energy value matched filtering calculation data are latched, and threshold passing identification is performed in the current short code period.
Compared with the prior art, the invention has the advantages that:
(1) the invention provides a method for fusion processing of bit synchronization and frame synchronization of spread spectrum signals, which is characterized in that aiming at two conditions of each bit initial position, the two conditions are respectively accumulated with correlation values and then are respectively detected synchronously, at the moment, the demodulation signal-to-noise ratio is improved, the error symbol is reduced, and the synchronization probability is greatly improved; for the case that each data bit contains a plurality of correlation integration periods, the demodulation signal-to-noise ratio can be improved by accumulating each case where the bit start position exists.
(2) The matched filtering detection of the correlation value energy provided by the invention needs to adjust the size of the detection threshold in time according to the size of the signal power, but the signal enters the stable tracking time at the moment, the correlation value can fluctuate occasionally, the judgment threshold is difficult to set, and the requirement of the energy matched filtering on the threshold can be properly reduced by increasing the calculation of the symbol matched filtering. The judgment condition at the moment needs to simultaneously satisfy that the energy matching filtering calculation and the symbol matching filtering calculation are larger than a threshold, so that the probability of signal synchronization is improved;
(3) the processing method provided by the invention can simultaneously detect bit synchronization and frame synchronization, and compared with the conventional processing method for performing frame synchronization after bit synchronization, the processing method shortens the synchronization time. The method is not only suitable for burst spread spectrum signals, but also suitable for continuous spread spectrum signals, and the FPGA is simple to realize, occupies less resources and has better actual measurement effect.
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FIG. 1 is a flow chart of a frame synchronization and bit synchronization fusion processing method provided by the present invention;
Detailed Description
A method for fusion processing of bit synchronization and frame synchronization of spread spectrum signals, as shown in fig. 1, includes the following steps:
(1) dividing a spread spectrum signal to be processed in a digital signal processing channel into N short code periods by taking time T as a time interval, wherein one symbol comprises E short code periods, and the length of a frame header is Q, namely Q symbols are included;
(2) starting from the first short code period, continuously integrating the E short code periods to obtain a first correlation value A1, starting from the E +1 short code period, continuously integrating the E short code periods to obtain a second correlation value A2, and so on, accumulating corresponding one integrated correlation value AQ in each E adjacent short code periods to obtain Q correlation values A1 and A2 … … AQ, and demodulating the Q correlation values to obtain symbols S1 and S2 … … SQ of the Q correlation values;
(3) starting from the second short code period, continuously integrating the E short code periods to obtain a first correlation value B1, starting from the E +1 short code period, continuously integrating the E short code periods to obtain a second correlation value B2, and so on, accumulating corresponding one integral correlation value BQ in each E adjacent short code periods to obtain Q correlation values B1 and B2 … … BQ, and demodulating the Q correlation values to obtain symbols Y1 and Y2 … … YQ of the Q correlation values;
(4) by analogy, starting from the xth short code period, continuously integrating the E short code periods to obtain a first correlation value X1, starting from the xth +1 short code period, continuously integrating the E short code periods to obtain a second correlation value X2, by analogy, accumulating corresponding integrated correlation value XQ in each E adjacent short code periods to obtain Q correlation values X1 and X2 … … XQ, and simultaneously demodulating the Q correlation values to obtain symbols X1 and X2 … … XQ of the Q correlation values;
(5) carrying out symbol matching filtering data measurement on the symbol correlation value sequence obtained in the step (2), the step (3) and the step (4), if the measured data is greater than a symbol matching filtering calculation threshold value, carrying out correlation energy value matching filtering data measurement, if the measured data is greater than the correlation energy value matching filtering calculation threshold value, entering the step (6), otherwise, if X is greater than 2, carrying out the step (4) again; if X is 2, the step (3) is carried out again;
(6) if the calculated symbol matched filtering calculation data and the related energy value matched filtering calculation data in the step (5) are both greater than the symbol matched filtering calculation threshold value or the related energy value matched filtering calculation threshold value for the first time in the calculation process, recording the initial position of the current short code period, latching the current symbol matched filtering calculation data and the related energy value matched filtering calculation data at the same time, and performing threshold passing identification in the current short code period;
(7) and (4) if the data obtained in the step (5) is not larger than the threshold value for the first time, comparing the data with the short code period marked in the step (6), if the data is larger than the latched data value in the step (6), canceling the threshold-crossing identifier of the previous short code period, marking the current latched data value and the short code period, and if the data does not exceed the threshold-crossing identifier for the first time in ten continuous measurements, stopping the calculation.
In the step (5), the threshold of the symbol matched filtering is related to the frame error rate index, the frame error rate is mainly composed of two performance indexes, and the step of calculating the threshold value of the symbol matched filtering data is as follows:
(a) and (3) calculating the probability of missing detection of symbol matching filtering, wherein the calculation formula is as follows:
in the formula, Pl is the probability of missed detection, PeIn order to receive the error probability of the symbol, s is the length of a frame header sequence to be checked, k is the maximum number of allowed errors during checking, r is an integral variable of a calculus, and the variation range is 0-k;
(b) and calculating the false alarm probability of symbol matching filtering, wherein the calculation formula is as follows:
in the formula, Pf is false alarm probability;
comparing step (a) with step (b) reveals that when the determination condition is relaxed, that is, when k increases, the false alarm probability increases, but the false detection probability decreases. The frame error rate is equal to the cumulative sum of the false alarm rate and the missed detection rate;
(c) and calculating the symbol matching filtering frame error rate according to the following calculation formula:
P＝Pl+Pf
in the formula, P is the symbol matched filtering frame error rate, i.e. the symbol matched filtering threshold.
In the step (5), the calculation method of the energy matching filtering calculation threshold value Z is that
Z＝P·O
Where O is the average of the accumulated energy in a single symbol.
In the step (7), starting from a pseudo code initial position where the symbol matched filtering calculation result and the correlation value energy matched filtering calculation result are firstly greater than the threshold value, sequentially delaying the initial position for E-1 short code periods, selecting and outputting the maximum value of the correlation value energy matched filtering calculation result for E times, and outputting the initial position of the short code period at the same time, wherein at this time, the signal bit synchronization and the frame synchronization are synchronized successfully at the same time.
The following is further illustrated with reference to specific examples:
when the frame header length is 31ms and one symbol length is 1ms, the relationship graph of the missed detection rate, the false alarm rate, the frame error rate and the number of fault tolerance is as follows:
TABLE 1 relationship between frame error rate and error tolerance number when the frame header is 31ms long
| Number of fault tolerance | Probability of missed detection | Probability of false alarm | Frame error rate |
| 3 | 3.2×10-3 | 2.3×10-6 | 3.2×10-3 |
| 4 | 3.4×10-4 | 1.7×10-5 | 3.6×10-4 |
| 5 | 2.9×10-5 | 9.6×10-5 | 1.3×10-4 |
In the actual engineering, a symbol matching filtering missing detection probability calculation formula and a symbol matching filtering false alarm probability calculation formula need to be simulated to obtain an upper table, a frame error rate index calculated according to the upper table simulation is compared with an actual project, and the frame error rate corresponding to the fault-tolerant number is selected to be smaller than an engineering index, wherein the energy matching filtering threshold determination method comprises the following steps:
the energy matched filter computation threshold is the product of the symbol matched filter computation threshold and the average worth of the accumulated energy of a single symbol. And obtaining the average value of the accumulated energy of the single symbol in actual engineering, wherein the average value of the energy corresponding to each short code sequence period is O.
Those skilled in the art will appreciate that those matters not described in detail in the present specification are well known in the art.
Claims (5)
1. A fusion processing method of spread spectrum signal bit synchronization and frame synchronization is characterized by comprising the following steps:
(1) dividing a spread spectrum signal to be processed into N short code periods by taking time T as a time interval, and setting a symbol to comprise E short code periods;
(2) starting from the first short code period, integrating each symbol to obtain a corresponding symbol correlation value, demodulating each symbol correlation value to obtain a corresponding symbol correlation value sequence, and recording the length of the symbol correlation value sequence as Q, namely comprising Q symbols;
(3) starting from the second short code period, integrating each symbol to obtain a corresponding symbol correlation value, and demodulating each symbol correlation value to obtain a corresponding symbol correlation value sequence;
(4) starting from the Xth short code period, integrating each symbol to obtain a corresponding symbol correlation value, and demodulating each symbol correlation value to obtain a corresponding symbol correlation value sequence, wherein X is a positive integer greater than 2;
(5) measuring symbol matched filtering data and related energy value matched filtering data of a currently obtained symbol related value sequence, if and only if the symbol matched filtering data and the related energy value matched filtering data exceed threshold values, entering a step (6), otherwise, changing the value of X and performing the step (4) again, wherein the energy matched filtering calculation threshold is the product of the symbol matched filtering calculation threshold and the average value of the accumulated energy of a single symbol;
(6) if the data obtained in the step (5) exceeds the threshold value, judging whether the symbol matching filtering data of the currently obtained symbol correlation value sequence and the related energy value matching filtering data both exceed the threshold value for the first time, if so, performing threshold passing identification on the current short code period and latching the current symbol matching filtering and related energy value matching filtering data value, and if not, entering the step (7);
(7) and (4) respectively comparing the symbol matched filtering data and the related energy value matched filtering data of the currently obtained symbol related value sequence with the latching data in the step (6), and canceling the threshold passing identifier of the previous short code period, marking the identifier at the current short code period and latching the current matched filtering data value if and only if the two matched filtering data are respectively greater than the latching data value in the step (6).
2. The method according to claim 1, wherein the method comprises the following steps: in the step (2), a specific method for obtaining the related symbol value sequence is as follows:
starting from the first short code period, continuously integrating the E short code periods to obtain a first correlation value A1, starting from the E +1 short code period, continuously integrating the E short code periods to obtain a second correlation value A2, and so on, accumulating corresponding one integrated correlation value AQ in each E adjacent short code periods to obtain Q correlation values A1 and A2 … … AQ, and demodulating the Q correlation values to obtain symbols S1 and S2 … … SQ of the Q correlation values.
3. The method according to claim 1, wherein the method comprises the following steps: in the step (5), the step of calculating the symbol matching filter data threshold value is:
(a) and (3) calculating the probability of missing detection of symbol matching filtering, wherein the calculation formula is as follows:
in the formula, Pl is the probability of missed detection, PeIn order to receive the error probability of the symbol, s is the length of a frame header sequence to be checked, k is the maximum number of allowed errors during checking, r is an integral variable of a calculus, and the variation range is 0-k;
(b) and calculating the false alarm probability of symbol matching filtering, wherein the calculation formula is as follows:
in the formula, Pf is false alarm probability;
(c) and calculating the symbol matching filtering frame error rate according to the following calculation formula:
P＝Pl+Pf
in the formula, P is the symbol matched filtering frame error rate, i.e. the symbol matched filtering threshold.
4. The method according to claim 3, wherein the method comprises: in the step (5), the calculation method of the energy matching filtering calculation threshold value Z is that
Z＝P·O
Where O is the average of the accumulated energy in a single symbol.
5. The method according to claim 1, wherein the method comprises the following steps: in the step (7), the symbol matched filtering data and the related energy value matched filtering data of the currently obtained symbol related value sequence are calculated and compared with the latched data in the step (6) for ten times, and if the values of the data latched in the step (6) are not exceeded, the calculation is stopped.
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