CN110531323B - Reference signal reconstruction method suitable for MIMO/OFDM external radiation source radar - Google Patents

Reference signal reconstruction method suitable for MIMO/OFDM external radiation source radar Download PDF

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CN110531323B
CN110531323B CN201910797910.XA CN201910797910A CN110531323B CN 110531323 B CN110531323 B CN 110531323B CN 201910797910 A CN201910797910 A CN 201910797910A CN 110531323 B CN110531323 B CN 110531323B
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CN110531323A (en
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饶云华
胡海霞
王雅莉
潘登
周健康
聂文洋
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Shenzhen Research Institute of Wuhan University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/28—Details of pulse systems
    • G01S7/2813—Means providing a modification of the radiation pattern for cancelling noise, clutter or interfering signals, e.g. side lobe suppression, side lobe blanking, null-steering arrays
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/28—Details of pulse systems
    • G01S7/285—Receivers
    • G01S7/292—Extracting wanted echo-signals
    • G01S7/2923—Extracting wanted echo-signals based on data belonging to a number of consecutive radar periods
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/35—Details of non-pulse systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/35—Details of non-pulse systems
    • G01S7/352—Receivers
    • G01S7/354—Extracting wanted echo-signals

Abstract

The invention discloses a method for reconstructing a radar reference signal of an external radiation source suitable for MIMO/OFDM, which comprises the steps of firstly realizing frame synchronization, symbol synchronization and frequency synchronization by using a preamble training sequence in a direct wave signal, then eliminating intersymbol interference and subcarrier interference caused by multipath, Doppler frequency shift and the like by using a pilot frequency through a channel estimation algorithm, then recovering original data by using a maximum likelihood decoding algorithm, obtaining a bit stream with low BER after decoding and error correction, then recoding the clean bit stream to generate a transmitting end signal, finally analyzing a self-fuzzy function of the transmitting end signal, and inhibiting a fuzzy function secondary peak and a side lobe. Compared with the method for directly acquiring the reference signal, the method provided by the invention improves the purity of the reference signal, is beneficial to target detection of a radar system, and is simple to implement.

Description

Reference signal reconstruction method suitable for MIMO/OFDM external radiation source radar
Technical Field
The invention belongs to the technical field of external radiation source radars and the technical field of communication, relates to the acquisition of a reference signal of a radar receiving end, and adopts a reference signal acquisition and purification method based on demodulation, remodulation and correction.
Background
In the field of radar, the working environment of active radar is more and more unsafe by the existing multiple anti-radar technologies, and even faces huge examination. Meanwhile, along with the gradual opening of low-altitude airspace in China, the civil aviation industry is rapidly developed, but effective low-altitude airspace monitoring and controlling means have many defects. The appearance of the external radiation source radar provides a new solution for solving the dilemma faced by the traditional active radar at the present stage, and simultaneously better conforms to the requirements of the era. The third party radiation sources utilized by the exogenous radar are mainly: digital Television Broadcasting Terrestrial DVB-T (Digital Video Broadcasting-Terrestrial), Digital Television Terrestrial Broadcasting DTMB (Digital Television Terrestrial Multimedia Broadcasting), China Mobile Multimedia Broadcasting CMMB (Chinese Mobile Multimedia Broadcasting), FM Broadcasting, Digital Audio Broadcasting DAB (Digital Audio Broadcasting), LTE (Long Term Broadcasting).
The signals based on the IEEE wireless local area network standard (802.11n) adopt a MIMO/OFDM coding scheme, which is greatly different from other radiation source characteristics. The signal is popularized in main cities at home and abroad at present, and the through-wall detection by using the signal as an external radiation source has natural advantages: the coverage of 802.11n signals is wide, and wireless networks are covered from public areas such as airports, coffee bars, restaurants, fast food restaurants, hotels and department stores to private areas such as families, schools, government agencies and even spacecrafts, so that the 802.11n exogenous radar has a plurality of application scenes; meanwhile, the number of 802.11n access points is large, thereby being beneficial to the networking detection of an external radiation source radar, improving the detection range and reducing the cost; compared with the signals researched before, the 802.11n signals have higher bandwidth, excellent wall-through performance, smaller blind areas and better distance resolution; the 802.11n signal has 2.4G and 5G double-frequency modes, so that double-frequency detection can be realized in the future.
The external radiation source radar generally has two channels, one is a monitoring channel and receives a target scattered signal, and the other is a reference channel and receives a direct wave emitted by the radiation source and is used as a reference signal to perform matched filtering with the monitoring signal. The quality of the reference signal has a great influence on the matched filtering result, and it is very important to acquire a clean reference signal.
The first mode is a mode of directly acquiring the reference signal, namely, the reference signal is directly pointed to the direction of a transmitting station at a receiving end through a directional reference antenna, and the received reference channel signal is the reference signal; the other reference signal acquisition mode is that the reference channel signal is processed by 'demodulating-remodulating' to reconstruct a transmitting signal so as to extract a purer direct wave signal as a reference signal; the invention provides a 'demodulation-remodulation-correction' method for reconstruction on the basis of the traditional 'demodulation-remodulation' mode, thereby reducing the secondary peak and the side lobe of a signal fuzzy function and improving the detection performance.
The reconstruction needs to sequentially carry out synchronization, channel estimation, MIMO space-time decoding, demapping, deinterleaving, decoding error correction and error correction on a received signal to obtain a correct bit stream, then carries out correction according to the characteristics of a transmitted signal to reduce secondary peak and sidelobe suppression, and finally generates an 802.11n reference signal according to the transmitted signal generation step. The synchronization mainly includes frame synchronization, symbol synchronization and frequency synchronization. The frame synchronization is to roughly estimate the starting position of a frame signal; symbol synchronization is mainly to find the starting point of the OFDM symbol; the frequency synchronization has different processing algorithms according to the magnitude of the frequency offset, mainly for correcting the frequency offset. Synchronization is a precondition for subsequent processing performed by a receiving end, and is inaccurate, which may cause that subsequent steps such as channel estimation cannot be performed normally, so that synchronization is very important for signal reconstruction.
Therefore, the invention provides a reference signal reconstruction method suitable for an 802.11n external radiation source radar based on the characteristics of a signal frame structure and the orthogonality of OFDM signals.
Disclosure of Invention
Aiming at the problem that the purity of a reference signal directly obtained by an external radiation source radar is not high, the invention provides a reference signal purification method based on demodulation-remodulation-correction reconstruction.
The technical scheme adopted by the invention is as follows: a reference signal reconstruction method suitable for an 802.11n external radiation source radar comprises the following steps:
step 1, roughly detecting a reference signal in a signal stream through frame synchronization, and finding out a rough initial position of a signal frame, specifically: detecting a frame starting point by using 10 identical short training sequences in direct wave signal preamble through a delay correlation frame synchronization algorithm, and judging according to judgment measurement, namely the change of a superposition value of correlation values received on each antenna, wherein the position where a judgment measurement peak value appears is the starting point of a frame;
step 2, carrying out coarse frequency offset estimation on the signal in the step 1 by using a data-aided method, and correcting larger frequency offset existing in the signal;
step 3, finding out the initial position of the OFDM symbol by using a symbol synchronization algorithm, correlating the initial position with a received sampling sequence by using a delay synchronization correlation algorithm and a long training sequence, and estimating the initial position of the OFDM symbol according to decision measurement;
step 4, carrying out correlation by adopting a long training sequence in a frame structure, and estimating decimal frequency offset existing in the system;
step 5, adopting a pilot frequency-based channel estimation method, firstly estimating a channel value at a pilot frequency position, and then calculating channel values of other subcarriers by utilizing an interpolation algorithm;
step 6, performing space-time decoding, and recovering the original data stream by adopting a maximum likelihood decoding algorithm;
and 7, generating a reference signal according to the correct bit stream obtained in the step 6 and the emission signal generation step, and after the reference signal is generated, correcting the reference signal according to fuzzy function analysis to realize side peak suppression and side lobe suppression of the fuzzy function.
Further, the specific implementation of step 1 is as follows,
for the sampling sequence r (n) of the received signal, the starting point of the frame in step 1 is calculated by the following formula,
Figure BDA0002181471480000031
Figure BDA0002181471480000032
Figure BDA0002181471480000033
Figure BDA0002181471480000034
wherein k represents the number of receiving antennas; l is a delay correlation accumulated value of the short training sequence; n represents an index value of a subcarrier; d is the length of the sliding window, which is consistent with the length value of the short training sequence; ck(n) is a time-delayed autocorrelation function, Pk(n) is the energy of the received signal, cor (n) is the decision metric of a single antenna, Tr is the number of transmitting antennas, M is the decision metric of multiple antennas, and when the decision metric rapidly increases to a peak value, the position where the peak value appears is the start of the frame.
Further, the specific implementation manner in step 2 is as follows,
let the nth sample of the mth OFDM symbol of the transmitted signal on the ith transmitting end antenna be si(m, n), then the corresponding received symbol is represented as:
Figure BDA0002181471480000035
after passing through the MIMO channel, the signal received at the jth receiving antenna is represented as:
Figure BDA0002181471480000041
at the transmitting end, the short training sequences are not different as a whole, and only have a difference in phase, so the delay related values are expressed as follows:
Figure BDA0002181471480000042
because the MIMO system employs multiple receiving antennas, on the basis of obtaining the value of a single receiving antenna, it is also necessary to sum the values to obtain a final decision variable, and then the obtained frequency offset value is:
Figure BDA0002181471480000043
wherein, yi(m, n) are received symbol sample values, fcFor the carrier frequency of transmission, TsFor a sampling interval, TxFor the number of transmit antennas, w is additive white Gaussian noise, rj(m, n) is the signal on the jth receiving antenna, zjIs a delay related value, L is a delay related accumulated value of the short training sequence, D is a length value of the short training sequence, fΔFor the frequency difference between the receiving carrier and the transmitting carrier, the frequency offset value is
Figure BDA0002181471480000044
Is an angular representation of the phase difference, ranging from (-pi, pi);
therefore, the obtained coarse frequency offset estimation range is as follows:
Figure BDA0002181471480000045
further, the specific implementation manner of step 3 is as follows,
in the two-transmitting two-receiving system under 40MHz mode in 802.11n protocol standard, the length of cyclic shift is 0 ns-400 ns in sequence, the second receiving chain is connected with the previous oneThe ratio is advanced by 8 samples, if the starting point of the L-LTF is set to correspond to nsFor each sample, the correlation between the long training sequence and the received sample sequence is expressed as:
Figure BDA0002181471480000046
in the above formula, rkThe sample sequence received by the kth receive chain is shown,
Figure BDA0002181471480000047
complex conjugates of long training sequences;
the decision metric at this time is:
M2(n)＝|Ck(n)|2+|Ck(n-8)|2
the starting point of the OFDM symbol is estimated as:
Figure BDA0002181471480000051
further, the specific implementation manner of step 4 is as follows,
the fine carrier frequency offset algorithm adopts a long training sequence in a frame structure to be related to a received signal, adopts an HT-Mixed frame format of an 802.11n WiFi signal, and adopts an L-LTF sequence in the frame format, wherein the L-LTF consists of a guard interval and two sections of long training sequences;
Figure BDA0002181471480000052
Figure BDA0002181471480000053
where Λ is the correlation function, r (n)L+ k) is the complete long training portion, r (n) is the received signal, nLFor long training sequence symbol starting points, TFFTFor the length of the long training sequence, N is the number of subcarriers, kThe frequency deviation estimated value of the decimal carrier is epsilon for the index value corresponding to the subcarrier of the long training symbolf；
Therefore, the obtained precision frequency offset estimation range is as follows:
Figure BDA0002181471480000054
the range of fine carrier frequency offset estimation is at most half of the subcarrier spacing.
Further, the specific implementation manner of step 5 is as follows,
assuming that the transmitted sequence is matrix X, the received signal is matrix Y, the channel matrix is H, the channel noise Z satisfies E { Z (k) } 0,
Figure BDA0002181471480000055
the entire system model is then represented as follows:
Y＝XH+Z
the cost function of the channel matrix is then:
J(H)＝||Y-XH||2＝YHY-YHXH-HHXHY+HHXHXH
in the above formula, Y and X are the receiving and transmitting end signals respectively;
the above equation is subjected to partial derivation and the value is equal to 0, i.e.:
Figure BDA0002181471480000056
can obtain XHY＝XHXH, further simplified to give:
H＝(XHX)-1XHY＝X-1Y
the expected representation of H is as follows:
E(H)＝E(X-1Y)＝E(X-1(XH+Z))＝E(H+X-1Z)＝E(H)
j (H) the cost function of the channel matrix, Y and X are the receiving and transmitting end signals respectively, and the expectation of H is E (H); let Hp(k) For estimated pilot subcarriersThe channel value of wave k, L is the number of pilot frequencies in an OFDM symbol, and the channel value estimated at the pilot frequency is firstly measured
Figure BDA0002181471480000061
Taking IDFT to obtain hp(k) (ii) a Then in the time domain by passing hp(k) The zero-filling mode obtains a time domain signal of
Figure BDA0002181471480000062
Wherein the number of zero padding is the number of subcarriers N minus the number of pilot frequencies; last pair of
Figure BDA0002181471480000063
Obtaining the channel estimation value by N-point DFT conversion
Figure BDA0002181471480000064
The mean square error of the LS channel estimate is expressed as follows:
Figure BDA0002181471480000065
wherein, deltaz，δxRespectively the variance of the signal X and the noise Z.
Further, the specific implementation manner of step 6 is as follows,
the transmitting end adopts the STBC scheme proposed by Alamouti, the data transmitted on two antennas of the transmitting end is transmitted after orthogonal coding, and the coding matrix is expressed as:
Figure BDA0002181471480000066
in the above formula, s0,s1-two consecutive symbols after modulation;
(·)*-a complex conjugate operation;
by means of the coding matrix, in the first time interval T, s0，s1Are transmitted simultaneously by antennas 1, 2, respectively; during the second timeSpacer T-s* 1，s* 0Are transmitted simultaneously by antennas 1, 2, respectively; then, there are not only 2 transmitting signals on the receiving end antenna, but also noise, because the space-time block code adopts orthogonal coding, the receiving end can adopt maximum likelihood decoding algorithm to recover the original data, and when the receiving end is at time T and T + T, the received signals are as follows:
r0＝r(t)＝h0s0+h1s1+n0
Figure BDA0002181471480000071
in the above formula, h0(t),h1(t) -channels between the transceiving antennas;
n0,n1-the received noise;
the received signals are linearly combined to obtain the following expression:
Figure BDA0002181471480000072
Figure BDA0002181471480000073
further simplification can be achieved:
Figure BDA0002181471480000074
Figure BDA0002181471480000075
in the above formula, the first and second carbon atoms are,
Figure BDA0002181471480000076
-equivalent white gaussian noise in the first, second symbol period;
and further simplifying the judgment rule according to the maximum likelihood criterion to obtain:
Figure BDA0002181471480000077
Figure BDA0002181471480000078
in the above formula, s is a set of constellation points in the modulation constellation of M system, hi,jRepresenting the channel between the ith transmit antenna and the jth receive antenna.
Furthermore, the specific implementation manner of correcting the reference signal according to the fuzzy function analysis in step 7 to realize the side peak suppression and the side lobe suppression of the fuzzy function is as follows,
the position and amplitude of the secondary peak in the fuzzy function divide the secondary peak into two categories, one category of secondary peak is positioned at the symmetrical position near the main peak, and the amplitudes of the two peaks are close to the amplitude of the main peak and are caused by leading symbols; the amplitude of the other type of secondary peak is obviously smaller than that of the main peak, and the secondary peak is distributed more dispersedly and is caused by cyclic prefix;
aiming at the first class, a method of removing the leading symbols is adopted to suppress the secondary peaks generated by the leading symbols; and for the second type, removing a secondary peak caused by the cyclic prefix by adopting a cyclic prefix zero setting method, and simultaneously carrying out invalid subcarrier processing to inhibit side lobes.
Compared with the prior art, the reference signal obtained by the method has high purity and outstanding advantages, has positive effect on improving the detection performance of a radar system, and has great significance for the practical application of an external radiation source radar.
Drawings
FIG. 1: is the structure diagram of the MIMO system of the embodiment of the invention;
FIG. 2: is a method flow diagram of an embodiment of the invention;
FIG. 3: is a specific algorithm flow chart of frame synchronization;
FIG. 4: is a channel estimation method;
FIG. 5: is a transmitting end signal generating flow;
FIG. 6: is a map of the source signal blur function;
FIG. 7: is the long training sequence delay autocorrelation;
FIG. 8: is the short training sequence delay autocorrelation;
FIG. 9: is a graph of the signal ambiguity function after processing the preamble;
FIG. 10: is a graph of the fuzzy function after processing the preamble and cyclic prefix;
FIG. 11: is a graph of the signal ambiguity function after processing the preamble and cyclic prefix and invalid subcarriers.
Detailed Description
In order to facilitate the understanding and implementation of the present invention for those of ordinary skill in the art, the present invention is further described in detail with reference to the accompanying drawings and examples, it is to be understood that the embodiments described herein are merely illustrative and explanatory of the present invention and are not restrictive thereof.
Fig. 1 and fig. 2 are a MIMO structure diagram and a method flowchart implemented by the present invention, in the embodiment of the present invention, a signal is a signal in an IEEE 802.11n protocol standard OFDM mode, a modulation mode is 16-QAM, a subcarrier interval is 312.5KHz, and a center frequency is 2.4 GHz. The invention provides a reference signal reconstruction method suitable for an 802.11n external radiation source radar, which comprises the following steps of:
step 1: the signal in the signal stream is roughly detected by frame synchronization to find out the approximate starting position of the signal frame. The method comprises the steps of utilizing 10 identical short training sequences in 802.11n preambles, detecting a frame synchronization starting point through a delay correlation frame synchronization algorithm, judging according to the change of decision metrics, namely the superposition value of correlation values received on each antenna, and determining that the position where a decision metric peak value appears is the starting point of a frame, as shown in fig. 3.
For the sampling sequence r (n) of the received signal, the starting point of the frame in step 1 is calculated by the following formula:
Figure BDA0002181471480000091
Figure BDA0002181471480000092
Figure BDA0002181471480000093
Figure BDA0002181471480000094
where k represents the number of receive antennas, here taken to be 2; l is a short training sequence delay correlation accumulated value, and 5 is selected; n represents an index value of the subcarrier, ranging from 0 to 127; d is the length of the sliding window, is consistent with the length value of the short training sequence, and 32 is taken; ck(n) is a time-delayed autocorrelation function, Pk(n) is the energy of the received signal, cor (n) is the decision metric of a single antenna, Tr is the number of transmitting antennas, 2 is generally taken, M is the decision metric of a plurality of antennas, when the decision metric rapidly increases to a peak value, the position where the peak value appears is the start point of a frame, and a specific algorithm flow chart of frame synchronization is shown in fig. 3;
step 2: and (3) carrying out coarse frequency offset estimation on the signal in the step (1) by using a data-aided method, and correcting larger frequency offset existing in the signal.
Let the nth sample of the mth OFDM symbol of the transmitted signal on the ith transmitting end antenna be si(m, n), then the corresponding received symbol may be represented as:
Figure BDA0002181471480000095
after passing through the MIMO channel, the signal received at the jth receiving antenna can be represented as:
Figure BDA0002181471480000096
at the transmitting end, the short training sequences are not different as a whole, and only have a difference in phase, so the delay related value can be expressed as follows:
Figure BDA0002181471480000101
since the MIMO system employs multiple receiving antennas, it is necessary to sum the values of the receiving antennas to obtain a final decision variable. The resulting frequency offset value is then:
Figure BDA0002181471480000102
wherein, yi(m, n) are received symbol sample values, fcFor the carrier frequency of transmission, TsFor a sampling interval, TxFor the number of transmit antennas, w is additive white Gaussian noise, rj(m, n) is the signal on the jth receiving antenna, zjIs a delay related value, L is a delay related accumulated value of the short training sequence, D is a length value of the short training sequence, fΔFor the frequency difference between the receiving carrier and the transmitting carrier, the frequency offset value is
Figure BDA0002181471480000103
The range is represented by the angle of phase difference (- π, π).
Therefore, the obtained coarse frequency offset estimation range is as follows:
Figure BDA0002181471480000104
and step 3: the initial position of the OFDM symbol is found out by utilizing a symbol synchronization algorithm, a delay synchronization correlation algorithm is adopted, a long training sequence is correlated with a received sampling sequence, and the starting point of the OFDM symbol is estimated according to the decision metric.
As with frame synchronization, since the received signal is the sum of the signals on multiple transmit antennas, and to prevent beamforming, a round robin is introducedThe ring shift distinguishes signals on different transmitting antennas, so the symbol synchronization algorithm of the single-input single-output SISO system cannot be applied to the MIMO system, and corresponding improvement must be carried out by combining the characteristics of the MIMO system. The invention mainly aims at a two-transmitting and two-receiving system under a 40MHz mode in an 802.11n protocol standard, the length of cyclic shift is 0ns to 400ns in sequence, a second receiving link leads 8 samples compared with a previous receiving link, and if the starting point of L-LTF is set to correspond to nsSample, then correlating the long training sequence with the received sample sequence at this time can be expressed as:
Figure BDA0002181471480000105
in the above formula, rkThe sample sequence received by the kth receive chain is shown,
Figure BDA0002181471480000106
is the complex conjugate of a long training sequence.
The decision metric at this time is:
M2(n)＝|Ck(n)|2+|Ck(n-8)|2
the start of the OFDM symbol can be estimated as:
Figure BDA0002181471480000111
and 4, step 4: and (4) fine frequency offset estimation. After the integer-times carrier frequency offset is synchronized, because the estimation algorithm has limited precision, the signal still has residual frequency offset, and the residual carrier frequency offset needs to be estimated by utilizing the fine carrier frequency offset. The residual carrier frequency offset not only causes amplitude distortion of the carrier frequency component, but also causes phase distortion. If the correction is not carried out, the decoding correctness can be directly influenced. The invention adopts HT-Mixed frame format of 802.11n WiFi signal, selects L-LTF sequence in frame format, the L-LTF is composed of guard interval and two sections of long training sequence,
Figure BDA0002181471480000112
Figure BDA0002181471480000113
where Λ is the correlation function, r*(nL+ k) is the complete long training portion, r (n) is the received signal, nLFor long training sequence symbol starting points, TFFTIs the length of the long training sequence, N is the number of subcarriers, k is the index value of the subcarrier corresponding to the long training symbol, and the decimal carrier frequency offset estimation value is epsilonf；
Therefore, the obtained precision frequency offset estimation range is as follows:
Figure BDA0002181471480000114
the range of fine carrier frequency offset estimation is at most half of the subcarrier spacing.
And 5: the channel estimation method based on the pilot frequency is adopted, firstly, the channel value at the pilot frequency position is estimated, and then the channel values of other subcarriers are calculated by utilizing an interpolation algorithm.
Assuming that the transmitted sequence is matrix X, the received signal is matrix Y, the channel matrix is H, the channel noise Z satisfies E { Z (k) } 0,
Figure BDA0002181471480000115
the entire system model can then be expressed as follows:
Y＝XH+Z
the cost function of the channel matrix is then:
J(H)＝||Y-XH||2＝YHY-YHXH-HHXHY+HHXHXH
in the above formula, Y and X are the transceiver end signals, respectively.
The above equation is subjected to partial derivation and the value is equal to 0, i.e.:
Figure BDA0002181471480000121
can obtain XHY＝XHXH, further simplified to give:
H＝(XHX)-1XHY＝X-1Y
the expectation of H can be expressed as follows:
E(H)＝E(X-1Y)＝E(X-1(XH+Z))＝E(H+X-1Z)＝E(H)
wherein J (H) the cost function of the channel matrix, Y, X are the receiving and transmitting end signals respectively, the expectation of H is E (H), the specific channel estimation method is shown in FIG. 4, and H in FIG. 4p(k) For the estimated channel value of the pilot subcarrier k, L is the number of pilots in one OFDM symbol. The algorithm first estimates the channel value at the pilot
Figure BDA0002181471480000122
Taking IDFT to obtain hp(k) (ii) a Then in the time domain by passing hp(k) The zero-filling mode obtains a time domain signal of
Figure BDA0002181471480000123
Wherein the number of zero padding is the number of subcarriers N minus the number of pilot frequencies; last pair of
Figure BDA0002181471480000124
Obtaining the channel estimation value by N-point DFT conversion
Figure BDA0002181471480000125
The mean square error of the LS channel estimate is expressed as follows:
Figure BDA0002181471480000126
wherein, deltaz，δxAre respectively signals X andvariance of the noise Z.
Step 6: performing space-time decoding after channel estimation, and recovering the original data stream by adopting a maximum likelihood decoding algorithm;
the transmitting end adopts the STBC scheme proposed by Alamouti, and the data transmitted on the two antennas of the transmitting end is transmitted after orthogonal coding. Its coding matrix can be expressed as:
Figure BDA0002181471480000131
in the above formula, s0,s1-modulating the two subsequent symbols
(·)*-complex conjugate operation
By means of the coding matrix, in the first time interval T, s0，s1Are transmitted simultaneously by antennas 1, 2, respectively; a second time interval T, -s* 1，s* 0Are transmitted simultaneously by antennas 1, 2, respectively. Then there are not only 2 transmitted signals on the receive antenna, but also noise. Because the space-time block code adopts orthogonal coding, the receiving end can adopt the maximum likelihood decoding algorithm to recover the original data. At times T and T + T, the receiving end receives the following signals:
r0＝r(t)＝h0s0+h1s1+n0
Figure BDA0002181471480000132
in the above formula, h0(t),h1(t) -channels between Transmit-receive antennas
n0,n1-received noise
The received signals are linearly combined to obtain the following expression:
Figure BDA0002181471480000133
Figure BDA0002181471480000134
further simplification can be achieved:
Figure BDA0002181471480000135
Figure BDA0002181471480000136
in the above formula, the first and second carbon atoms are,
Figure BDA0002181471480000137
-equivalent white gaussian noise in the first, second symbol period.
Further simplification of the decision rule according to the maximum likelihood criterion can result in:
Figure BDA0002181471480000138
Figure BDA0002181471480000141
in the above formula, s is a set of constellation points in the modulation constellation of M system, hi,jRepresenting the channel between the ith transmit antenna and the jth receive antenna.
And 7: the recovery of the original data stream, i.e. the resulting correct bit stream, can be obtained from the space-time decoding output of step 6. Then, re-modulating according to the transmission signal generation step to generate an original transmission signal, modifying the re-generated transmission signal to obtain a reconstructed reference signal, and according to the 802.11n standard, the transmission signal re-generation/re-modulation process is as shown in fig. 5, which specifically includes the following steps:
(1) scrambling by Scrambler: the transmission data is scrambled by xoring the scrambling sequence with the transmission data, thus avoiding long sequences of 0 or 1. The scrambling sequence is generated by the following formula:
S(x)＝x7+x4+1
(2) encoder split of Encoder for Encoder Parser: the scrambled data is subjected to a division process because the number of LDPC encoders does not exceed 1, but the number of BBC encoders may be 1 or 2.
(3) FEC Encoder coding: the function is to encode the data after being shunted by the encoder.
(4) Stream Parser spatial Stream splitting: and distributing the coded code words to each spatial stream according to a fixed sequence. The number of input streams generated by spatial stream splitting is not fixed, and the number of input streams is changed along with the change of the constellation point mapping mode.
(5) Interleaver interleaving: data can burst errors in the transmission process, so that a decoder at a receiving end has great difficulty in decoding. Interleaving after encoding can avoid such a situation. The interleaving process is not used in LDPC coding, but is used only in BCC coding. The original order of the bits is changed to prevent long sequences of adjacent noisy bits from entering the BCC decoder, reducing the impact on the decoding block.
(6) Constellation mapper Constellation mapping: mapping the bit sequence in each spatial stream to constellation points (complex numbers) i.e. modulating the input data.
(7) An STBC (Space-time block code Space-time coding) module: STBC coding is used when the spatial stream is smaller than the space-time stream. STBC is formed by encoding NssExpansion of strip spatial streams to NstsA space-time stream.
(8) CSD (Cyclic Shift Diversity): preventing the formation of additional interfering beams.
(9) Spatial Mapping: the function is to map the space-time streams into transmission chains. There are three mapping methods:
direct mapping (direct mapping): the constellation points of each space-time stream are directly mapped to a transmitting link, wherein the number of data streams is equal to the number of transmitting antennas, and a mapping matrix is an identity matrix, namely, data is mapped to the antennas one by one.
Spatial extension (spatial extension): when the spatial stream is less than or equal to the number of antennas, all the constellation point vectors from the space-time stream are expanded through matrix multiplication to generate the input of all the transmit chains.
Beamforming (beamforming): as with spatial spreading, the input to all transmit chains is generated by multiplying the constellation point vector from each space-time stream by a matrix consisting of steering vectors (steeringvectors) by a matrix multiplication operation.
(10) Inverse Discrete Fourier Transform (IDFT): a set of constellation points is transformed to the time domain.
(11) Insert GI And Window inserts a guard interval GI And the GI takes the last quarter of the data symbols of the OFDM symbol. Windowing to enhance out-of-passband attenuation.
An 802.11n signal can be generated according to the above steps, but the signal needs to be continuously corrected to meet the requirement of being used as an external radiation source radar detection signal. This is because the external radiation source radar acquires target information by correlating the reference signal with the monitor signal. And performing cross correlation on the two signals to obtain a cross-fuzzy function, and extracting a target distance and a speed parameter from the position where the peak value of the cross-fuzzy function appears.
Fig. 6 shows a diagram of a cross-ambiguity function of a signal generated by the method of fig. 5, and it can be seen from fig. 6 that some secondary peaks appear in the ambiguity function according to a certain rule in addition to the primary peak, the existence of the secondary peaks may affect the determination of the target position, and when the peak value of the secondary peak is too large, the primary peak may be submerged, so to accurately detect the target, the direct wave must be preprocessed, that is, the secondary peaks appearing in the ambiguity function are suppressed to reduce the effect of the secondary peaks on the target detection.
The secondary peaks can be classified into two categories according to the position and amplitude of the secondary peaks in fig. 6, wherein one category of secondary peaks is located at the symmetrical position near the main peak, and the amplitudes of the two peaks are closer to the amplitude of the main peak, such as the distance spectrum shown in fig. 6 (b); the secondary peaks of the other type have significantly smaller amplitudes than the primary peaks and are distributed more scattered, such as the doppler domain in the range-doppler spectrogram shown in fig. 6 (a).
First-type secondary peaks: analysis and suppression of side peaks caused by pilot symbols
Some of the frame formats of the 802.11n signal are preamble symbols, and for example, in the HT-Mixed frame format, the preamble symbols are composed of L-STF, L-LTF, HT-STF, and HT-LTF, and the occurrence position of each frame is fixed, so that the peak occurs when the same symbol is self-correlated.
For a long training sequence, the sequence is divided into two parts, L-LTF and HT-LTF. For the L-LTF, it consists of two identical long symbols, each symbol having a duration of 3.2us, and after autocorrelation of the L-LTF, as shown in fig. 7(a), two peaks appear after the L-LTF correlation, the positions where the two peaks appear are the 1 st point and the 128 th point, respectively, and the two peaks are spaced by 128 sampling points. For HT-LTF, the number of space-time streams studied in this paper is 2, then HT-LTF is composed of 2 data field long training sequences, and the duration of each symbol is 3.2us, and after the HT-LTF is auto-correlated, as shown in fig. 7(b), two peaks appear after HT-LTF correlation, the positions where two peaks appear are respectively the 1 st point and the 128 th point, and the interval between two peaks is also 128 sampling points.
Similarly, for short training sequences, L-STF and HT-STF are included. The L-STF consists of 10 short symbols, each symbol is completely the same and has the duration of 0.8us, after the L-STF is subjected to autocorrelation, ten peaks appear after the autocorrelation as shown in FIG. 8(a), the positions of the peaks are respectively the 1 st point, the 33 th point, the 65 th point, the 97 th point, the 129 th point, the 161 th point, the 193 th point, the 225 th point, the 257 th point and the 289 th point, and 32 sampling points are arranged between two adjacent peaks. For HT-STF, 4 short training sequences each having a duration of 0.8us, except for the guard interval, are obtained, and after autocorrelation of HT-STF, as shown in fig. 8(b), four peaks appear after correlation, the positions of the peaks are respectively the 1 st point, the 33 rd point, the 65 th point, and the 97 th point, and the interval between two adjacent peaks is 32 sampling points.
Based on the above analysis, each sequence in the leader induces a secondary peak after auto-correlation. In order to eliminate the secondary peak caused by the leading symbol, namely to remove the correlation between the leading symbols, the invention adopts a method of removing the leading symbol to suppress the secondary peak generated by the leading symbol. The elimination of the preamble symbols results in an 802.11n ambiguity function as shown in fig. 9. The doppler domain in the range-doppler spectrum of fig. 9(a) does not have small regular secondary peaks, which have been suppressed, and the range spectrum of fig. 9(b) does not have small secondary peaks on either side of the main peak, which have also been suppressed. Comparing fig. 6 and fig. 9, it can be seen that the secondary peak caused by the preamble after the preamble is removed is well suppressed, i.e. the secondary peak with a small amplitude relative to the main peak in fig. 7 does not exist. But now there are still secondary peaks in the 802.11n signal ambiguity function and the remaining secondary peaks are stronger than those caused by the preamble, which is mainly caused by the cyclic prefix.
Secondary peaks of the second type: analysis and suppression of secondary peak caused by cyclic prefix
After the effective part of the OFDM symbol is processed by coding, interleaving and the like, the data is random, and the correlation between the parts does not have secondary peaks. But the cyclic prefix is composed of a forward shift of the end portion of the valid data field, so that the correlation of this portion of data causes a corresponding secondary peak. As can be seen from fig. 9, there are significant secondary peaks on either side of the main peak and at a distance of 32 units from the main peak. Since the cyclic prefix also occurs at a distance of 32 from the cell, this secondary peak is largely due to the inserted cyclic prefix.
In order to eliminate the secondary peak caused by the cyclic prefix and also remove the correlation, the present invention adopts the same method as suppressing the secondary peak caused by the preamble symbol, and the cyclic prefix is processed here. The result of processing the preamble symbol and cyclic prefix in the 802.11n signal is shown in fig. 10, in which the secondary peak in the range-doppler spectrogram of fig. 10(a) is suppressed, and the secondary peak in the range spectrogram of fig. 10(b) is also suppressed.
Comparing fig. 8 with fig. 10, it can be seen that the secondary peak at distance unit 32 has disappeared, that is, the secondary peak caused by the cyclic prefix is removed by zeroing the cyclic prefix. At the same time can alsoIt is seen that the 802.11n fuzzy function after the preamble removing and the cyclic prefix zero setting process is in the shape of a drawing pin, and only tau is 0, fdThere is a main peak at 0 and the remaining secondary peaks are suppressed, but the sidelobes are still relatively high.
The reason for this is that side lobes appear due to the presence of null subcarriers. 802.11n uses HT-Mixed frame format, 40MHz bandwidth, the number of valid data subcarriers is 108, and after processing invalid subcarriers, a blurring function is obtained as shown in fig. 11, where both secondary peaks and side lobes in the range-doppler spectrogram of fig. 11(a) can be found to be suppressed, and both secondary peaks and side lobes in the range spectrogram of fig. 11(b) can be found to be suppressed. Comparing fig. 10 and fig. 11, it can be seen that the blur function is in the pin shape, and meets the requirement as the radar signal source of the external radiation source.
After secondary peak suppression and sidelobe treatment, an ideal pin-type fuzzy function is obtained, the false alarm probability is greatly reduced, and the target detection performance is greatly improved.
The above description of the preferred embodiments is intended to be illustrative, and not to be construed as limiting the scope of the invention, which is defined by the appended claims, and all changes and modifications that fall within the metes and bounds of the claims, or equivalences of such metes and bounds are therefore intended to be embraced by the appended claims.

Claims (7)

1. A reference signal reconstruction method suitable for MIMO/OFDM external radiation source radar is characterized by comprising the following steps:
step 1, roughly detecting a reference signal in a signal stream through frame synchronization, and finding out a rough initial position of a signal frame, specifically: detecting a frame starting point by using 10 identical short training sequences in direct wave signal preamble through a delay correlation frame synchronization algorithm, and judging according to judgment measurement, namely the change of a superposition value of correlation values received on each antenna, wherein the position where a judgment measurement peak value appears is the starting point of a frame;
step 2, carrying out coarse frequency offset estimation on the signal in the step 1 by using a data-aided method, and correcting larger frequency offset existing in the signal;
the specific implementation in step 2 is as follows,
let the nth sample of the mth OFDM symbol of the transmitted signal on the ith transmitting end antenna be si(m, n), then the corresponding received symbol is represented as:
Figure FDA0003075053720000011
after passing through the MIMO channel, the signal received at the jth receiving antenna is represented as:
Figure FDA0003075053720000012
at the transmitting end, the short training sequences are not different as a whole, and only have a difference in phase, so the delay related values are expressed as follows:
Figure FDA0003075053720000013
because the MIMO system employs multiple receiving antennas, on the basis of obtaining the value of a single receiving antenna, it is also necessary to sum the values to obtain a final decision variable, and then the obtained frequency offset value is:
Figure FDA0003075053720000014
wherein, yi(m, n) are received symbol sample values, fcFor the carrier frequency of transmission, TsFor a sampling interval, TxFor the number of transmit antennas, w is additive white Gaussian noise, rj(m, n) is the signal on the jth receiving antenna, zjIs a delay related value, L is a delay related accumulated value of the short training sequence, and D is the short training sequenceColumn length value, fΔFor the frequency difference between the receiving carrier and the transmitting carrier, the frequency offset value is
Figure FDA0003075053720000021
angle (×) is an angular representation of the phase difference, ranging from (-pi, pi);
therefore, the obtained coarse frequency offset estimation range is as follows:
Figure FDA0003075053720000022
step 3, finding out the initial position of the OFDM symbol by using a symbol synchronization algorithm, correlating the initial position with a received sampling sequence by using a delay synchronization correlation algorithm and a long training sequence, and estimating the initial position of the OFDM symbol according to decision measurement;
step 4, carrying out correlation by adopting a long training sequence in a frame structure, and estimating decimal frequency offset existing in the system;
step 5, adopting a pilot frequency-based channel estimation method, firstly estimating a channel value at a pilot frequency position, and then calculating channel values of other subcarriers by utilizing an interpolation algorithm;
step 6, performing space-time decoding, and recovering the original data stream by adopting a maximum likelihood decoding algorithm;
and 7, generating a reference signal according to the correct bit stream obtained in the step 6 and the emission signal generation step, and after the reference signal is generated, correcting the reference signal according to fuzzy function analysis to realize side peak suppression and side lobe suppression of the fuzzy function.
2. The method for reconstructing the reference signal suitable for the MIMO/OFDM external radiation source radar as claimed in claim 1, wherein: the specific implementation of step 1 is as follows,
for the sampling sequence r (n) of the received signal, the starting point of the frame in step 1 is calculated by the following formula,
Figure FDA0003075053720000023
Figure FDA0003075053720000024
Figure FDA0003075053720000025
Figure FDA0003075053720000026
wherein k represents the number of receiving antennas; l is a delay correlation accumulated value of the short training sequence; n represents an index value of a subcarrier; d is the length of the sliding window, which is consistent with the length value of the short training sequence; ck(n) is a time-delayed autocorrelation function, Pk(n) is the energy of the received signal, cor (n) is the decision metric of a single antenna, Tr is the number of transmitting antennas, M is the decision metric of multiple antennas, and when the decision metric rapidly increases to a peak value, the position where the peak value appears is the start of the frame.
3. The method for reconstructing the reference signal suitable for the MIMO/OFDM external radiation source radar as claimed in claim 2, wherein: the specific implementation of step 3 is as follows,
in a two-transmission two-reception system under a 40MHz mode in an 802.11n protocol standard, the length of cyclic shift is 0ns to 400ns in sequence, a second receiving link leads a previous receiving link by 8 samples, and if the starting point of an L-LTF is set to correspond to nsFor each sample, the correlation between the long training sequence and the received sample sequence is expressed as:
Figure FDA0003075053720000031
in the above formula, rkIs shown asThe sample sequence received by the kth receive chain,
Figure FDA0003075053720000032
complex conjugates of long training sequences;
the decision metric at this time is:
M2(n)＝|Ck(n)|2+|Ck(n-8)|2
the starting point of the OFDM symbol is estimated as:
Figure FDA0003075053720000033
4. the method of claim 3, wherein the method comprises the following steps: the specific implementation of step 4 is as follows,
the fine carrier frequency offset estimation algorithm adopts a long training sequence in a frame structure to be related to a received signal, adopts an HT-Mixed frame format of an 802.11n WiFi signal, and adopts an L-LTF sequence in the frame format, wherein the L-LTF consists of a guard interval and two sections of long training sequences;
Figure FDA0003075053720000034
Figure FDA0003075053720000035
where Λ is the correlation function, r*(nL+ k) is the complete long training portion, r (n) is the received signal, nLFor long training sequence symbol starting points, TFFTIs the length of the long training sequence, N is the number of subcarriers, k is the index value of the subcarrier corresponding to the long training symbol, and the decimal carrier frequency offset estimation value is epsilonf；
Therefore, the obtained precision frequency offset estimation range is as follows:
Figure FDA0003075053720000041
the range of fine carrier frequency offset estimation is at most half of the subcarrier spacing.
5. The method of claim 4, wherein the method comprises the following steps: the specific implementation of step 5 is as follows,
assuming that the transmitted sequence is matrix X, the received signal is matrix Y, the channel matrix is H, the channel noise Z satisfies E { Z (k) } 0,
Figure FDA0003075053720000042
the entire system model is then represented as follows:
Y＝XH+Z
the cost function of the channel matrix is then:
J(H)＝||Y-XH||2＝YHY-YHXH-HHXHY+HHXHXH
in the above formula, Y and X are the receiving and transmitting end signals respectively;
the above equation is subjected to partial derivation and the value is equal to 0, i.e.:
Figure FDA0003075053720000043
can obtain XHY＝XHXH, further simplified to give:
H＝(XHX)-1XHY＝X-1Y
the expected representation of H is as follows:
E(H)＝E(X-1Y)＝E(X-1(XH+Z))＝E(H+X-1Z)＝E(H)
j (H) the cost function of the channel matrix, Y and X are the receiving and transmitting end signals respectively, and the expectation of H is E (H); let Hp(k) For estimated pilot sub-carrier kThe channel value, L, is the number of pilots in an OFDM symbol, and the channel value estimated at the pilot is first determined
Figure FDA0003075053720000044
Taking IDFT to obtain hp(k) (ii) a Then in the time domain by passing hp(k) The zero-filling mode obtains a time domain signal of
Figure FDA0003075053720000045
Wherein the number of zero padding is the number of subcarriers N minus the number of pilot frequencies; last pair of
Figure FDA0003075053720000046
Obtaining the channel estimation value by N-point DFT conversion
Figure FDA0003075053720000047
The mean square error of the LS channel estimate is expressed as follows:
Figure FDA0003075053720000051
wherein, deltaz，δxRespectively the variance of the signal X and the noise Z.
6. The method of claim 5, wherein the method comprises the following steps: the specific implementation of step 6 is as follows,
the transmitting end adopts the STBC scheme proposed by Alamouti, the data transmitted on two antennas of the transmitting end is transmitted after orthogonal coding, and the coding matrix is expressed as:
Figure FDA0003075053720000052
in the above formula, s0,s1-two consecutive symbols after modulation;
(·)*-a complex conjugate operation;
by means of the coding matrix, in the first time interval T, s0，s1Are transmitted simultaneously by antennas 1, 2, respectively; a second time interval T, -s* 1，s* 0Are transmitted simultaneously by antennas 1, 2, respectively; then, there are not only 2 transmitting signals on the receiving end antenna, but also noise, because the space-time block code adopts orthogonal coding, the receiving end can adopt maximum likelihood decoding algorithm to recover the original data, and when the receiving end is at time T and T + T, the received signals are as follows:
r0＝r(t)＝h0s0+h1s1+n0
Figure FDA0003075053720000053
in the above formula, h0(t),h1(t) -channels between the transceiving antennas;
n0,n1-the received noise;
the received signals are linearly combined to obtain the following expression:
Figure FDA0003075053720000054
Figure FDA0003075053720000055
further simplification can be achieved:
Figure FDA0003075053720000061
Figure FDA0003075053720000062
in the above formula, the first and second carbon atoms are,
Figure FDA0003075053720000063
-equivalent white gaussian noise in the first, second symbol period;
and further simplifying the judgment rule according to the maximum likelihood criterion to obtain:
Figure FDA0003075053720000064
Figure FDA0003075053720000065
in the above formula, s is a set of constellation points in the modulation constellation of M system, hi,jRepresenting the channel between the ith transmit antenna and the jth receive antenna.
7. The method for reconstructing the reference signal suitable for the MIMO/OFDM external radiation source radar as claimed in claim 1, wherein: the specific implementation manner of correcting the reference signal according to the fuzzy function analysis in the step 7 to realize the secondary peak suppression and the side lobe suppression of the fuzzy function is as follows,
the position and amplitude of the secondary peak in the fuzzy function divide the secondary peak into two categories, one category of secondary peak is positioned at the symmetrical position near the main peak, and the amplitudes of the two peaks are close to the amplitude of the main peak and are caused by leading symbols; the amplitude of the other type of secondary peak is obviously smaller than that of the main peak, and the secondary peak is distributed more dispersedly and is caused by cyclic prefix;
aiming at the first class, a method of removing the leading symbols is adopted to suppress the secondary peaks generated by the leading symbols; and for the second type, removing a secondary peak caused by the cyclic prefix by adopting a cyclic prefix zero setting method, and simultaneously carrying out invalid subcarrier processing to inhibit side lobes.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP4148463A1 (en) * 2021-09-10 2023-03-15 Nxp B.V. A radar system, a radar arrangement, and a radar method for concurrent radar operations

Families Citing this family (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111007475B (en) * 2019-12-11 2023-06-06 西安电子科技大学 LTE external radiation source radar frequency domain fuzzy auxiliary peak suppression method
CN113009462A (en) * 2019-12-20 2021-06-22 华为技术有限公司 Data processing method, device and equipment
CN111585740B (en) * 2020-04-01 2022-02-08 西安电子科技大学 Transmission signal synchronization processing method, system, storage medium, program, and terminal
CN112511470B (en) * 2020-12-04 2022-04-05 上海交通大学 Channel estimation method and device
CN114916009A (en) * 2021-02-10 2022-08-16 华为技术有限公司 Signal processing method and device
CN113281732B (en) * 2021-05-27 2023-03-24 华中科技大学 MIMO radar target positioning method and system based on space-time coding
CN114205199B (en) * 2021-11-30 2023-10-20 成都中科合迅科技有限公司 WIFI signal identification method in complex electromagnetic environment

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104502900A (en) * 2015-01-13 2015-04-08 武汉大学 Single-frequency network radar multi-target tracking method
CN105676199A (en) * 2015-12-31 2016-06-15 天津大学 Single channel LTE radar system based on communication/ radar integration
CN105891817A (en) * 2016-06-08 2016-08-24 中国人民解放军海军航空工程学院 Distributed passive radar target detection method under direct wave-free condition
CN106970382A (en) * 2017-03-22 2017-07-21 武汉大学 One kind is based on external illuminators-based radar unmanned plane real-time monitoring system and method
CN108549048A (en) * 2018-03-23 2018-09-18 武汉大学 A kind of multifrequency WiFi external illuminators-based radars coherent processing method
CN109660478A (en) * 2018-12-10 2019-04-19 长安大学 A kind of timing frequency synchronous method based on improved Park frequency domain training sequence
CN109738868A (en) * 2018-12-21 2019-05-10 武汉大学 A kind of external illuminators-based radar non homogeneous clutter suppression method based on channel identification
CN110109094A (en) * 2019-03-28 2019-08-09 西南电子技术研究所（中国电子科技集团公司第十研究所） The detection of multi-receiver station single frequency network external illuminators-based radar maneuvering target and tracking

Family Cites Families (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7248559B2 (en) * 2001-10-17 2007-07-24 Nortel Networks Limited Scattered pilot pattern and channel estimation method for MIMO-OFDM systems
FR2834072B1 (en) * 2001-12-26 2006-08-04 Onera (Off Nat Aerospatiale) FALSE REJECTION IN PASSIVE SIGNAL RADAR RECEPTOR TO OFDM WITH ANTENNA NETWORK
US8248975B2 (en) * 2005-09-06 2012-08-21 Nippon Telegraph And Telephone Corporation Wireless transmitting apparatus, wireless receiving apparatus, wireless transmission method, wireless reception method, wireless communication system, and wireless communication method
CN101076001B (en) * 2006-05-15 2011-03-02 中兴通讯股份有限公司 Method for estimating channel based on orthogonal frequency division multiplexing system
JP5142379B2 (en) * 2008-03-19 2013-02-13 パナソニック株式会社 Mobile station apparatus, base station apparatus, and communication control method for radio communication system
CN102571650B (en) * 2011-12-20 2014-06-18 东南大学 Self-adapting channel estimating method applied to 3GPP LTE system
CN106487735A (en) * 2015-09-01 2017-03-08 中兴通讯股份有限公司 A kind of frequency deviation estimating method and device
US10419177B2 (en) * 2016-03-22 2019-09-17 Samsung Electronics Co., Ltd. Signal transmitting and receiving methods in a filtering-based carrier modulation system and apparatuses thereof

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104502900A (en) * 2015-01-13 2015-04-08 武汉大学 Single-frequency network radar multi-target tracking method
CN105676199A (en) * 2015-12-31 2016-06-15 天津大学 Single channel LTE radar system based on communication/ radar integration
CN105891817A (en) * 2016-06-08 2016-08-24 中国人民解放军海军航空工程学院 Distributed passive radar target detection method under direct wave-free condition
CN106970382A (en) * 2017-03-22 2017-07-21 武汉大学 One kind is based on external illuminators-based radar unmanned plane real-time monitoring system and method
CN108549048A (en) * 2018-03-23 2018-09-18 武汉大学 A kind of multifrequency WiFi external illuminators-based radars coherent processing method
CN109660478A (en) * 2018-12-10 2019-04-19 长安大学 A kind of timing frequency synchronous method based on improved Park frequency domain training sequence
CN109738868A (en) * 2018-12-21 2019-05-10 武汉大学 A kind of external illuminators-based radar non homogeneous clutter suppression method based on channel identification
CN110109094A (en) * 2019-03-28 2019-08-09 西南电子技术研究所（中国电子科技集团公司第十研究所） The detection of multi-receiver station single frequency network external illuminators-based radar maneuvering target and tracking

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
IEEE802.11n信号解调的设计与实现;杨轶;《中国优秀硕士学位论文全文数据库 信息科技辑》;20180415;24-37、51-55 *
Signal Processing for Passive Radar Using OFDM Waveforms;Christian R. Berger;《IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING》;20100228;第4卷(第1期);226-238 *
WiFi外辐射源雷达参考信号重构及其对探测性能影响研究;饶云华;《雷达学报》;20160630;第5卷(第3期);284-292 *
基于IEEE802.lln的MIMO OFDM无线局域网系统的同步算法研究;张骋;《中国优秀硕士学位论文全文数据库 信息科技辑》;20080915;43-44 *
基于IEEE802.lln的MIMO一OFDM系统信道估计算法研究;翁维茜;《中国优秀硕士学位论文全文数据库 信息科技辑》;20080815;21-24 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP4148463A1 (en) * 2021-09-10 2023-03-15 Nxp B.V. A radar system, a radar arrangement, and a radar method for concurrent radar operations

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