CN112865882A - Anti-frequency-deviation DMR interphone signal rapid identification method - Google Patents

Abstract

The invention discloses a quick identification method of DMR interphone signals resisting frequency deviation, which comprises the steps of performing integral multiple and decimal multiple extraction on baseband data, performing normalization correlation on various locally reserved voice synchronous signals by a root-raised cosine filter, an FM demodulator and frequency deviation component precompensation after a DMR interphone suspected signal is found through monitoring, and finally judging whether the DMR interphone signal is a DMR interphone signal or not through a threshold. The method enhances the receiving range of the equipment to the signal frequency offset and improves the identification probability of the DMR interphone. The invention solves the problem that the DMR detection probability is reduced when frequency deviation exists, and is suitable for the field of wireless communication.

Description

Anti-frequency-deviation DMR interphone signal rapid identification method

Technical Field

The invention belongs to the technical field of signal detection, and particularly relates to a quick identification method for a DMR interphone signal resisting frequency deviation.

Background

When the wireless monitoring equipment scans the frequency band of the interphone, if suspicious wireless signals are found, frequency spectrum fine analysis is carried out to further clarify the bandwidth and the central frequency point of the signals. The central frequency point estimation often has frequency deviation, and the performance of synchronous correlation detection of the DMR signal is seriously reduced after the frequency deviation is more than 1 Khz.

Disclosure of Invention

The purpose of the invention is as follows: aiming at the defects, the invention provides the quick identification method of the DMR interphone signal with the frequency deviation resistance, which improves the success rate of identifying the DMR interphone signal by the monitoring equipment.

The technical scheme is as follows: the invention provides a quick identification method of a DMR interphone signal resisting frequency deviation, which is characterized by comprising the following steps:

(1) acquiring N times of oversampling signals;

(2) according to the oversampling multiple N, passing the sampling data p (N) through an FM demodulator, and outputting data q (N);

(3) filtering q (n) with a root raised cosine filter to obtain baseband data g (n)₁；

(4) According to the data g (n)₁Carrying out addition and subtraction of the offset numbers to obtain three groups of data to be detected, namely demodulation signal negative frequency offset precompensation, demodulation signal positive frequency offset precompensation and demodulation original signals;

(5) performing sliding normalization correlation operation on the three groups of data to be detected acquired in the step (4) and locally reserved 4 groups of DMR interphone voice synchronous data respectively;

(6) and (4) judging whether the related data peak value obtained by the operation in the step (5) exceeds a threshold, if so, judging that the signal is a DMR interphone signal, and if not, judging that the signal is not a DMR interphone signal.

Further, the specific steps of acquiring the N-fold oversampled signal in step (1) are as follows:

(1.1) monitoring a wireless environment with a large bandwidth;

(1.2) if suspicious signals are found in the frequency band of the DMR interphone, reducing the monitoring bandwidth and improving the frequency spectrum analysis precision;

(1.3) if the bandwidth of the signal conforms to the frequency spectrum characteristics of the DMR interphone, obtaining a central frequency point f₀；

(1.4) with f₀Performing down-conversion processing on data as a central frequency point to obtain baseband data { x (n) ═ 1,2, … … };

(1.5) the N-times oversampled signal { p (N) ═ 1,2,3, … } is obtained by integer-multiple decimation and fractional-multiple decimation.

Further, the output data g (n) in the step (3)₁In particular to

Further, the specific steps of obtaining three groups of data to be detected in the step (4) are as follows: demodulation data g (n)₁Minus offsetSetting the number fre2KOffset to { g (n)₂＝g(n)₁-fre2KOffset, n 1,2, … }, and the other group is demodulated data g (n)₁Adding an offset fre2KOffset to obtain { g (n)₃＝g(n)₁+ fre2KOffset, n ═ 1,2, … }, plus g (n)₁Three sets of data to be detected are formed.

Further, the specific steps of performing sliding normalization correlation operation on the three groups of data to be detected and the locally reserved 4 groups of DMR interphone voice synchronous data in the step (5) are as follows:

k is 0,2,4, …, W-1; w is the interval of the voice sync header, M is the length of the sync header

i is 1,2, 3; i is baseband three sets of data g (n)_iIndex

j is 1,2,3, 4; j is the four-voice synchronous head index

L ═ 0, 1, …, L-1; l is the number of periods of the voice sync signal for buffering the baseband data

By adopting the technical scheme, the invention has the following beneficial effects: the method can accurately detect the DMR interphone signal with high probability under the condition that frequency deviation within +/-3 KHz exists, simplifies the hardware design of monitoring equipment, reduces the precision requirement on frequency point estimation by a method of demodulating signals to add or subtract constants, does not need carrier synchronization, and reduces software complexity.

Drawings

FIG. 1 is a flow chart of a method of the present invention;

FIG. 2 is a signal power spectrum of a DMR intercom at a sampling rate of 38.4Khz in an exemplary embodiment;

FIG. 3 is a diagram illustrating an accumulated correlation between a DMR intercom signal and a local matching signal without frequency offset in an exemplary embodiment;

fig. 4 is a diagram illustrating the recognition rate under different frequency offset conditions in the specific embodiment.

Detailed Description

The present invention is further illustrated by the following examples, which are intended to be purely exemplary and are not intended to limit the scope of the invention, as various equivalent modifications of the invention will occur to those skilled in the art upon reading the present disclosure and fall within the scope of the appended claims.

As shown in fig. 1-4, the following description will be made by taking monitoring DMR interphone through mode slot1 communication operating at 409.7625MHz as an example:

step 1, monitoring 500MHz bandwidth of a wireless environment;

step 2, once a suspicious signal is found in the frequency band of the DMR interphone, reducing the monitoring bandwidth to 25MHz, and estimating the signal bandwidth to be 9.85 Khz;

step 3, the bandwidth of the signal accords with the frequency spectrum characteristics of the DMR interphone, and the central frequency point f is estimated₀＝409.761324MHz；

Step 4, using f₀Performing down-conversion processing on data as a central frequency point to obtain baseband data { x (n) }, wherein n is 1,2, … …, and the sampling frequency is 1M;

step 5, obtaining a 40K sampling signal by performing integral multiple extraction on 25 and obtaining a signal with a 38.4K sampling rate by performing fractional multiple extraction on 40/38.4, wherein the signal is an oversampling signal { p (N) } which is 8 times that of the oversampling signal, and N is 1,2,3, …, and fig. 2-4 is a signal power spectrum;

step 6, demodulating by the FM demodulator to obtain a demodulated signal { q (n) ═ 1,2,3, … };

and 7, according to the oversampling multiple N being 8, enabling the sampling data q (N) to pass through a root raised cosine filter h (N), wherein the oversampling multiple of the root raised cosine filter is 8, 49 tap coefficients are formed across 6 symbols, and the output data is recorded as

Step 8, demodulating data g (n)₁Subtracting the offset fre2 KOffset-5 to obtain { g (n)₂＝g(n)₁-fre2KOffset, n 1,2, … }, and the other group is demodulated data g (n)₁Adding an offset fre2 KOffset-5 to obtain { g (n)₃＝g(n)₁+ fre2KOffset, n ═ 1,2, … }, plus g (n)₁Forming three groups of data to be detected;

step 9,Using data { g (n)₁,g(n)₂,g(n)₃Voice synchronous data of 4 sets of local reserved DMR interphone (base station voice synchronization, mobile station voice synchronization, direct time slot1 voice synchronization, direct time slot 2 voice synchronization) { dmrSync (n)_jN is 1, 2., M, j is 1,2,3,4} to do sliding normalization correlation operation, the original voice synchronization header period interval is 13824 under the condition of 8 times oversampling, only the correlation value of even number position is calculated for reducing the operation amount: k is 0,2, …

k is 0,2,4, …, W-1; w is the interval of the voice sync header, M is the length of the sync header

i is 1,2, 3; i is baseband three sets of data g (n)_iIndex

j is 1,2,3, 4; j is the four-voice synchronous head index

L ═ 0, 1, …, L-1; l is the number of periods of the voice sync signal for buffering the baseband data

And overlap and accumulate the correlation result of 6 cycles, M192 is the synchronous head length of the pronunciation;

instep 10, the correlation data peak value of the sync header of the slot1 is shown in fig. 3-4, the normalized correlation value is 0.965, which exceeds the threshold of 0.65, and it is considered that the DMR interphone signal is identified.

Claims (5)

1. A quick identification method for DMR interphone signals resisting frequency deviation is characterized by comprising the following steps:

(1) acquiring N times of oversampling signals;

(2) demodulating the sampling data p (N) by an FM demodulator according to the oversampling multiple N, and recording the output data as q (N);

(3) q (n) is processed by a root raised cosine filter h (n) to obtain baseband data g (n)₁；

(4) According to the demodulated data g (n)₁Carrying out addition and subtraction of the offset numbers to obtain three groups of data to be detected, namely demodulation signal negative frequency offset precompensation, demodulation signal positive frequency offset precompensation and demodulation original signals;

(5) performing sliding normalization correlation operation on the three groups of data to be detected acquired in the step (4) and locally reserved 4 groups of DMR interphone voice synchronous data respectively;

(6) and (4) judging whether the related data peak value obtained by the operation in the step (5) exceeds a threshold, if so, judging that the signal is a DMR interphone signal, and if not, judging that the signal is not a DMR interphone signal.

2. The method for rapidly identifying the DMR interphone signal resisting the frequency offset as in claim 1, wherein the specific steps of obtaining the N-fold oversampled signal in step (1) are as follows:

(1.1) monitoring a wireless environment with a large bandwidth;

(1.2) if suspicious signals are found in the frequency band of the DMR interphone, reducing the monitoring bandwidth and improving the frequency spectrum analysis precision;

(1.3) if the bandwidth of the signal conforms to the frequency spectrum characteristics of the DMR interphone, obtaining a central frequency point f₀；

(1.4) with f₀Performing down-conversion processing on data as a central frequency point to obtain baseband data { x (n) ═ 1,2, … … };

(1.5) the N-times oversampled signal { p (N) ═ 1,2,3, … …, M } is obtained by integer-multiple decimation and fractional-multiple decimation.

3. The method as claimed in claim 1, wherein the output data g (n) in step (3) is the result of fast identification of DMR interphone signal against frequency deviation₁In particular to

4. The method for quickly identifying the DMR interphone signals resisting the frequency deviation as claimed in claim 1, wherein the specific steps of obtaining three sets of data to be detected in step (4) are as follows: demodulation data g (n)₁Subtracting the offset fre2KOffset to obtain { g (n)₂＝g(n)₁-fre2KOffset,n＝1,2,…The other group is the demodulation data g (n)₁Adding an offset fre2KOffset to obtain { g (n)₃＝g(n)₁+ fre2KOffset, n ═ 1,2, … }, plus g (n)₁Three sets of data to be detected are formed.

5. The method for rapidly identifying the DMR interphone signal with the anti-frequency offset function according to claim 1, wherein the step (5) of performing the sliding normalization correlation operation on the three sets of data to be detected and the locally retained 4 sets of DMR interphone voice synchronization data respectively comprises the following specific steps:

k is 0,2,4, …, W-1; w is the interval of the voice sync header, M is the length of the sync header

i is 1,2, 3; i is baseband three sets of data g (n)_iIndex

j is 1,2,3, 4; j is the four-voice synchronous head index

L ═ 0, 1, …, L-1; l is the number of periods of the voice sync signal that buffer the baseband data.

Images