Disclosure of Invention
The application provides a method for demodulating a signal by wiener filtering, which comprises the following steps:
removing the modulated signal of the pilot frequency to obtain channel information;
overlapping N continuous points of the channel information, and performing matrix combination on the overlapped signals to complete channel inversion to obtain frequency and initial phase;
extracting service signals to finish despreading the service signals;
and extracting the phase of each service signal, carrying out wiener filtering processing, predicting the phase of the service signal, correcting the phase of the service signal, and finally demodulating the signal correctly.
The method for demodulating the signal by adopting wiener filtering, which is described above, wherein N points of continuous channel information are overlapped, the overlapped signals are subjected to matrix combination, and channel inversion is completed to obtain frequency and initial phase, and the method specifically comprises the following sub-steps:
overlapping N continuous points of the channel information to obtain an overlapping value;
the phase of the superimposed value is calculated to obtain a phase angle_pre, and the phase angle_pre is adjusted;
and obtaining initial frequency and initial phase according to the adjusted phase composition matrix.
The method for demodulating a signal by wiener filtering as described above, wherein the phase angle_pre is adjusted, specifically, if the current phase is larger than PI, 2PI is subtracted, and if the current signal and the previous signal are smaller than PI, 2PI is added.
The method for demodulating signals by wiener filtering comprises the steps of extracting the phase of each service signal, carrying out wiener filtering processing, predicting the phase of the service signal, correcting the phase of the service signal, and finally demodulating the signals correctly, wherein the method specifically comprises the following sub-steps:
the initial frequency and the phase obtained by the synchronous head are used for obtaining the phase of the service signal needing initial calibration, and the phase of the following service signal is calibrated;
solving the phase of each service signal input per se, and then carrying out wiener filtering to obtain a new predicted phase;
performing phase correction on a signal input later by using the new predicted phase, thereby outputting a phase-corrected signal;
and demodulating the TS_symnum business data to obtain a final signal.
The method for demodulating signals by wiener filtering, which is described above, demodulates the ts_symnum service data to demodulate the final signals, specifically includes the following sub-steps:
acquiring a previously predicted phase;
calculating the phase of the current input signal;
normalizing the current phase direction and recording;
extracting Syn_num symbol time stamps adjacent to the current signal k;
matrix inversion is carried out according to the time stamp and the adjacent normalized input signal phase combination, and frequency variation and current initial phase are obtained through wiener filtering;
obtaining the current phase variation condition according to the frequency variation and the initial phase calculation;
the predicted phase modifies the current signal phase.
The application also provides a device for demodulating signals by wiener filtering, which comprises:
the pilot frequency modulation information processing module is used for removing the modulation signal of the pilot frequency to obtain channel information;
the frequency and initial phase calculation module is used for superposing N continuous points of the channel information, and performing matrix combination on the superposed signals to complete channel inversion to obtain frequency and initial phase;
the service signal despreading module is used for extracting service signals and completing despreading of the service signals;
and the wiener filtering processing module is used for extracting the phase of each service signal to carry out wiener filtering processing, predicting the phase of the service signal, correcting the phase of the service signal and finally correctly demodulating the signal.
The device for demodulating signals by wiener filtering as described above, wherein the frequency and initial phase calculation module is specifically configured to: overlapping N continuous points of the channel information to obtain an overlapping value; the phase of the superimposed value is calculated to obtain a phase angle_pre, and the phase angle_pre is adjusted; and obtaining initial frequency and initial phase according to the adjusted phase composition matrix.
The device for demodulating a signal by wiener filtering as described above, wherein in the frequency and initial phase calculation module, an initial frequency and an initial phase are obtained according to the adjusted phase composition matrix, and the device is specifically used for adjusting phase angle_pre, specifically subtracting 2PI if the current phase is large PI, and adding 2PI if the current signal and the previous signal are smaller than PI.
The device for demodulating the signal by adopting the wiener filtering is characterized in that the wiener filtering processing module is specifically used for obtaining the initial frequency and the phase through the synchronous head, so as to obtain the phase of the service signal needing initial calibration and calibrate the phase of the following service signal; solving the phase of each service signal input per se, and then carrying out wiener filtering to obtain a new predicted phase; performing phase correction on a signal input later by using the new predicted phase, thereby outputting a phase-corrected signal; and demodulating the TS_symnum business data to obtain a final signal.
The device for demodulating signals by adopting wiener filtering as described above, wherein in the wiener filtering processing module, the ts_symnum service data are demodulated, and a final signal is demodulated, which is specifically used for: acquiring a previously predicted phase; calculating the phase of the current input signal; normalizing the current phase direction and recording; extracting Syn_num symbol time stamps adjacent to the current signal k; matrix inversion is carried out according to the time stamp and the adjacent normalized input signal phase combination, and frequency variation and current initial phase are obtained through wiener filtering; obtaining the current phase variation condition according to the frequency variation and the initial phase calculation; the predicted phase modifies the current signal phase.
The beneficial effects realized by the application are as follows: by adopting the method, the correlation of the front and rear signals can be utilized to complete the demodulation of the signals, the phase of the signals can be estimated better, so that the signal information can be demodulated better, and compared with the signal demodulation in the prior art, the frequency offset estimation and the phase adjustment can be carried out on sampling points one by one, and the method can be suitable for the demodulation of a high-speed moving object better. Because the frequency offset of the signal is severely changed under the condition of high-speed movement and high local oscillation, the signal is difficult to adapt according to the existing algorithm, and the frequency offset estimation is adjusted in real time according to the input adjacent signal, so that the frequency offset can be optimally adapted to the change of the frequency offset.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
In the first embodiment of the present application, when burst spread spectrum communication occurs, a method for demodulating a signal by wiener filtering is provided, where a predicted phase of the signal is received by wiener filtering, and a phase of an input signal is corrected by the predicted phase, so as to obtain a demodulated signal, a frame structure of a burst spread spectrum communication system is shown in fig. 1, a preamble of 4096 chips is provided in front of each burst, after channel synchronization, modulation information of the preamble is removed to obtain h_sig, n=256 points are continuously superimposed on h_sig, 16 synchronization symbols are obtained, and the superimposed synchronization symbols are combined in a matrix to complete channel wiener filtering inversion to obtain an initial frequency w0 and an initial phase ph0, so as to obtain an initial frequency offset and an initial phase offset; and then carrying out carrier synchronous tracking on the data, firstly despreading the tracked signal, carrying out tracking estimation on the frequency offset and the phase offset of the despread service signal, compensating the data, and finally demodulating and outputting.
As shown in fig. 2, in the method for demodulating a signal by wiener filtering, a modulated signal of a pilot frequency is removed to obtain channel information h_sig, and then the following steps are executed:
step 210, overlapping continuous N points of the channel information h_sig, and performing matrix combination on the overlapped signals to complete channel inversion to obtain frequency w and initial phase ph0;
in this embodiment of the present application, N consecutive points of channel information h_sig are superimposed, and after the superimposition, syn_num signals are obtained, and these signals are combined in matrix, so as to complete channel wiener filtering inversion to obtain an initial frequency w0 and an initial phase ph0, and specifically includes the following sub steps:
step 211, overlapping N (n=space_len_syn_yasuo) points of the channel information h_sig to obtain an overlapping value corr_value;
step 212, performing phase calculation on the superposition value corr_value to obtain a phase angle_pre, and performing +12PI adjustment on the phase angle_pre;
the +12pi adjustment is performed on the phase angle_pre, specifically, if the current phase is larger than PI, 2PI is subtracted, and if the current signal and the previous signal are smaller than PI, 2PI is added, specifically, the following operations are implemented:
step 213, forming a matrix according to the adjusted phase angle_pre to obtain an initial frequency w and an initial phase ph0;
the initial frequency w and initial phase ph0 are obtained according to the following formula:
R(:,1)＝(-Syn_num+0.5:1:-.5)'；
R(:,2)＝ones(Syn_num,1)；
w＝inv(R'*R)*(R'*angle_pre)；
where w is a matrix of 1*2, w (1) is the initial frequency w0, and w (2) is the initial phase ph0.
Referring back to fig. 2, in step 220, the service signal is extracted to complete despreading of the service signal.
Step 230, extracting the phase of each service signal, then carrying out wiener filtering processing, finally predicting the phase of the service signal, correcting the phase of the service signal, and finally demodulating the signal correctly;
in this embodiment, the correct demodulation of the signal specifically includes the following sub-steps:
step 231, obtaining an initial frequency w0 and a phase ph0 through the synchronization head, thereby obtaining a phase phest of the service signal needing initial calibration, and calibrating the phase of the service signal at the back;
step 232, the phase angle_data input by each service signal is obtained, and then the new predicted phase_est is obtained through wiener filtering;
step 233, performing phase correction on the signal input later by using the new predicted phase_est, so as to output a signal after phase correction;
since the synchronization signal is a superposition of more sampling points per symbol, 4 times the number of superposition points per point of the service signal, the time stamp including the synchronization signal and the time signal is divided into two stages (recorded with the time axis t_rec):
t_rec＝[(-Syn_num+0.5：1：-.5)′；(1/4/2：1/4：1/4*TS_symNum)′]；
the phase of the Syn_num synchronization header symbols is calculated as follows:
cal_phase (1:syn_num) =w (1) × (-syn_num+0.5:1: -.5)' +w (2); i.e. current phase = frequency variation time stamp + initial phase;
step 234, demodulating the ts_symnum service data to obtain a final signal, which specifically includes the following sub-steps:
step1, acquiring a previously predicted phase;
step2, calculating the phase of the current input signal;
step3, carrying out normalization processing on the current phase direction and recording;
step4, extracting Syn_num symbol time stamps adjacent to the current signal k;
step5, performing matrix inversion according to the time stamp and the adjacent normalized input signal phase combination, and obtaining a frequency variation w (1) and a current initial phase w (2) by wiener filtering;
step6, calculating to obtain the current phase variation condition cal_phase (syn_num+k) =w (1) ×t_rec (syn_num+k) +w (2) according to the frequency variation and the initial phase;
step7, correcting the current signal phase by the predicted phase.
In addition, in the embodiment of the present application, in order to ensure the signal-to-noise ratio of the phase sequence, the despread data is accumulated by SP sampling points (SP is the spreading ratio), for example, the following operations of angle phase calculation are performed from the kth sampling point, that is:
S(k：k+8)＝[sum(Ck (1：SP))；sum(Ck (SP+1：2SP))；...；sum(Ck (8SP：9SP))；]
then set S (k) =sum (Ck (1：SP))，S(k+1)＝sum(Ck (SP+1：2SP))；After the phase of the despread signal is obtained, normalizing the phase direction of the input signal, wherein angle is a function used for obtaining the radian value of the phase angle in Matlab, namely:
if Pk (0)＞cal_phase(k)
to-be-estimated value omega1 ，ω2 Carrier frequency and phase respectively, and the corresponding time from P (0) to P (8) is t respectively0 To t8 The method can obtain:
ω1 tk+0 +ω2 ＝Pk (0)
ω1 tk+1 +ω2 ＝Pk (1)
…
ω1 tk+8 +ω2 ＝Pk (8)
the matrix operation can be obtained:
assume thatIs available in the form of
According to the wiener filter formula, where w1 is frequency, where w2 is phase,
available ω=ω1 And θ=ω2 The solution of wiener filtering is:
cal_phase(k+8)＝ω1 *tk+8 +ω2
the final phase corrected output signal Sout (k+8) is as follows:
cal_phase is the current phase variation situation.
Fig. 3 shows a graph of the radian of Pk (0) after normalization of the input signal direction and the phase cal-phase (k+8) curve after wiener filtering output, and from fig. 3, it can be known that the wiener filtered phase curve can stably track the angular variation of the input signal, so as to provide accurate determination for the subsequent revised signal direction.
Fig. 4 shows a comparison of signal constellations before and after Jing Weina filtering output, and as can be seen from fig. 4, the signal constellations are obviously aggregated after the wiener filter correlation processing, so that a good demodulation signal can be obtained.
By adopting the method for demodulating the signal by utilizing wiener filtering, the correlation of the front and rear signals can be utilized to complete the demodulation of the signal, and the phase of the signal can be estimated better, so that the signal information can be demodulated better, and compared with the signal demodulation in the prior art, the frequency offset estimation and the phase adjustment can be performed on sampling points one by one, and the method can be better suitable for demodulation of a high-speed moving object. Because the frequency offset of the signal is violent under the condition of high-speed movement and high local oscillation, the signal is difficult to adapt according to the existing algorithm, and the frequency offset estimation is adjusted in real time according to the input adjacent signal, so that the frequency offset can be optimally adapted to the frequency offset variation.
The foregoing examples are merely specific embodiments of the present application, and are not intended to limit the scope of the present application, but the present application is not limited thereto, and those skilled in the art will appreciate that while the foregoing examples are described in detail, the present application is not limited thereto. Any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or make equivalent substitutions for some of the technical features within the technical scope of the disclosure of the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the corresponding technical solutions. Are intended to be encompassed within the scope of this application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.