An initial angle search method and terminal for an array antenna time division system under strong interference

Abstract

The present invention discloses an initial angle search method and a terminal for a time-division system of an array antenna under strong interference. The array antenna includes multiple array elements. A search angle interval and a search duration are set. The local signal is received at the time of the transmitted signal within the search duration, and the covariance matrix and the optimal weight vector of the first local signal received by each array element are calculated; the optimal weight vectors on all array elements within the same search angle and the same search duration are weighted to calculate the peak power point and the maximum signal-to-noise ratio at this search angle; all search angles are traversed to obtain the maximum peak point and the highest signal-to-noise ratio point, and the corresponding search angle is the initial angle, and the corresponding optimal weight vector is the optimal weighting coefficient. The subsequent received signals are subjected to spatial domain filtering using the optimal weighting coefficient. After signal synchronization and frequency offset correction, the pilot part data of all array element antennas is correlated with the local pilot signal data, and signal equalization and demodulation processing are performed to eliminate interference and noise.

Description

Technical Field

[0001] The present invention relates to the technical field of ground-air communication, and particularly to an initial angle search method and a terminal for an array antenna time division system under strong interference. Background Art

[0002] In recent years, with the rapid development of the civil aviation industry, the flight flow has been increasing continuously, and the requirements for the control department have become higher and higher. Correspondingly, the requirements for control means have also become higher and higher. This is mainly reflected in the improvement of communication quality, the expansion of communication coverage, and the improvement of the stability and reliability of the communication system in ground-air command communication. However, the ground-air communication of China's civil aviation air traffic control is often interfered by radio, and normal communication cannot be guaranteed. Fundamentally solving how to obtain signals and process them under the interference state of civil aviation ground-air communication is an urgent problem to be solved at present. Summary of the Invention

[0003] The purpose of the present invention is to provide an initial angle search method and a terminal for an array antenna time division system under strong interference. According to the time division characteristics of communication signals, the search angle interval and search duration are set. Data is obtained by sliding synchronization within the search duration, and the data is calculated to obtain the peak power point, maximum signal-to-noise ratio, and steering vector α(θ 0 ) of the desired signal at each search angle. The angle corresponding to the maximum signal-to-noise ratio with the largest value is used as the initial angle, the optimal weighting value is calculated, the interference and noise in the signal data are excluded, the true azimuth angle of the aircraft is obtained, and at the same time, frequency offset modification, signal equalization, and demodulation processing are performed on the subsequent signals to improve the data processing accuracy.

[0004] In the first aspect, the above-mentioned invention purpose of the present invention is achieved through the following technical solutions:

[0005] An initial angle search method for an array antenna time division system under strong interference. The array antenna includes M*N array elements located in the XOY plane. The search angle interval and search duration are set. The local pilot signal is received at the transmission signal time within the search duration, and the covariance matrix and optimal weight vector of the first local signal received by each array element are calculated; within the same search angle and the same search duration, the vector signals on all array elements are weighted and combined to obtain the peak power point and maximum signal-to-noise ratio at this search duration and this search angle; all search angles are traversed to obtain the maximum peak point and the highest signal-to-noise ratio point, and the corresponding search angle is the initial angle, and the corresponding optimal weight vector is the optimal weighting coefficient. The subsequent received signals are spatially filtered with the optimal weighting coefficient. After signal synchronization and frequency offset correction, the pilot part data of all array element antennas is correlated with the local pilot signal data to obtain the final optimized weighting value, and signal equalization and demodulation processing are performed.

[0006] The present invention is further configured to include: a calculation duration, wherein the calculation duration is arranged at intervals with the search duration to form a search cycle; the search duration includes at least two receiving signal durations and at least one transmitting signal duration to ensure that there is a synchronization signal each time a sliding correlation occurs within the search duration.

[0007] The present invention is further configured as follows: within the same search angle and the same search duration, the data collected on all array elements form a complex vector with a length of ANT=M*N, and the covariance matrix R and the optimal weight vector W are calculated for each set of data. opt , obtain the optimal weight vector data set, weight all the optimal weight vector data to obtain the first signal; the local pilot signal received within the receiving time is continuously synchronously correlated with the first signal within the search time to obtain the second signal of the correlation peak point, and the peak power point, the maximum signal-to-noise ratio and the steering vector α(θ of the desired signal under the search angle are calculated based on the second signal of the correlation peak point. 0 ).

[0008] The present invention is further configured to: use the maximum value of the second signal of all relevant peak points at the same search angle and within the same search duration as the peak power point of the search angle and the search duration.

[0009] The present invention is further configured as follows: at the same search angle, within a time period of the length of the local pilot signal sequence, all first signals are conjugate correlated with the local pilot signal to obtain a third signal; the third signals in all time periods are processed, the average value is calculated, the absolute value is taken, and finally the square is obtained to obtain the first data; then, for the third signals in all time periods, the absolute value is first taken, the square operation is then performed, and the average value is calculated to obtain the second data; the second data is subtracted from the first data to obtain the third data; the ratio of the first data to the third data is calculated to obtain the fourth data at the search angle, and the maximum value of the fourth data within all search durations of the search angle is the maximum signal-to-noise ratio of the search angle.

[0010] The present invention is further configured to: traverse all search angles, obtain peak point data sets and maximum signal-to-noise ratio data sets corresponding to all search angles, take the maximum value in the peak point data set as the maximum peak point, and take the maximum value in the maximum signal-to-noise ratio data set as the highest signal-to-noise ratio.

[0011] The present invention is further configured to: calculate the weighting coefficient corresponding to the maximum peak point and the maximum signal-to-noise ratio point as the optimal weighting coefficient, perform spatial filtering on the ANT root array element antenna according to the optimal weighting coefficient, and obtain a signal for subsequent synchronization search and frequency offset measurement correction processing, determine the pilot data of the ANT root antenna according to the synchronization point, and perform subsequent calculations.

[0012] The present invention is further configured as follows: according to the optimal weighting system, the signals at subsequent reception times are weighted and combined to obtain a D signal, and the subsequent signals are synchronized and the frequency offset measurement is corrected; according to the synchronization signal, at the synchronization point, the pilot part data of the ANT root array element antenna is extracted and correlated with the local pilot signal data to obtain the final optimized weighting value Weightop; the Ka root antennas are combined into one channel to complete the subsequent signal equalization and demodulation processing.

[0013] The present invention is further configured as follows: a method for searching for the azimuth angle includes the following steps:

[0014] S1. Start;

[0015] S2. Set the search angle interval Keli and calculate the maximum number of search times; calculate W through LCMV within the calculation time opt , and search for the peak point according to W opt within the search duration;

[0016] S3. Determine whether the search angle is completed. If so, go to S8; if not, proceed to the next step;

[0017] S4. Collect the received signal, and according to the angle cycled to currently, obtain the steering vector α(θ 0 ) of the desired signal at this angle, perform LCMV calculation to obtain the weighting value W opt at this angle;

[0018] S5. According to the weighting value W opt at this angle, combine the data of the Ka root antennas of the received signal to obtain the first signal y1 sp (t) at this angle;

[0019] S6. The local pilot sequence slides and correlates within the set search duration Tsearch, and records the peak power point Peak sp obtained within the current search duration, and calculates the signal-to-noise ratio using the correlation information of the peak point;

[0020] S7. sp = sp + 1, update the search angle, and go to S3;

[0021] S8. Calculate the maximum value among the peak power points of all search angles and the maximum value among the signal-to-noise ratios, and obtain the corresponding weighting coefficient W opt O, that is, extract the optimal weighting value W opt O from the maximum value group;

[0022] S9. Adopt W opt O to weight and combine the signals at the subsequent UL moment to obtain a D signal;

[0023] S10. Synchronize subsequent signals and correct frequency offset measurement;

[0024] S11. According to the synchronization signal, extract the pilot part data of the ANT root array element antenna at the synchronization point, correlate it with the local pilot signal data, and obtain the final optimized weighting value Weightop;

[0025] S12. Combine the Ka root antennas into one channel to complete subsequent signal equalization and demodulation processing;

[0026] S13. End.

[0027] In a second aspect, the above object of the present invention is achieved by the following technical solutions:

[0028] An initial angle search terminal for an array antenna time division system under strong interference includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method described in this application is implemented.

[0029] Compared with the prior art, the beneficial technical effects of this application are as follows:

[0030] 1. This application calculates the maximum signal-to-noise ratio of the received local signals at different search angles and transmitted signals, obtains interference and noise signals, and eliminates interference and noise when receiving signals to improve signal quality;

[0031] 2. Further, this application calculates the peak power points at different search angles, obtains the angle corresponding to the maximum peak power point as the target signal angle to improve the reception efficiency;

[0032] 3. Further, this application processes subsequent signals based on the optimal weighting value, combines multiple antennas into one channel for signal equalization and demodulation, and improves the operation efficiency. Description of the Drawings

[0033] Figure 1 It is a schematic diagram of the structure of a ground-to-air communication system in a specific embodiment of this application;

[0034] Figure 2 It is a schematic diagram of the signal timing and calculation timing structure in a specific embodiment of this application;

[0035] Figure 3 It is a schematic diagram of signal processing according to the search angle in a specific embodiment of this application;

[0036] Figure 4 It is a schematic diagram of the signal processing flow structure in a specific embodiment of this application. Detailed Embodiments

[0037] The present invention will be further described in detail below with reference to the accompanying drawings.

[0038] A method for initial angle search of an array antenna time-division system under strong interference in the present application. The array antenna includes M*N array elements, which are located in the XOY plane. The array elements are equally spaced and distributed in a rectangle. The array element at one corner of the array is located at the origin O. The number of array elements on the Y-axis is M, and the number of array elements on the X-axis is N. The element spacing is d, and the coordinates of the array element are (x n , y m ). The angle between the signal incident direction and the Z-axis is . The angle between the projection of the incident direction in the XOY plane and the X-axis is θ. Selecting the origin as the reference point, the time delay difference between the signal reaching the array element (x n , y m ) and the signal reaching the origin is:

[0039]

[0040] In the formula, c is the speed of light.

[0041] The phase difference between the signal reaching the array element (c n , y m ) and the signal reaching the origin is:

[0042]

[0043] In the formula: f 0 is the incident signal frequency, and λ 0 is the incident signal wavelength.

[0044] Then, at time t, the signal vector received by the M*N array elements is:

[0045]

[0046]

[0047] In the formula, s 0 (t) represents the incident signal reaching the array element at the origin, is the steering vector of the incident signal.

[0048] x i,q (t) represents the incident signal of the antenna array element (i, q), represents the steering vector of the incident signal of the antenna array element (i, q), represents the angle of the incident signal of the antenna array element (i, q).

[0049] Among them, i = (1, 2,..., N), q = (1, 2,..., M).

[0050] In a time-division system, the local pilot signal received during signal transmission does not contain useful signals, only interference and noise signals. Calculate the covariance matrix for the first local signal and use the covariance matrix to update the optimal weight vector in real time. Based on the optimal weight vector, solve the linearly constrained minimum variance problem to form an algorithm for an adaptive beam based on the linearly constrained minimum variance criterion. By adjusting the weight vector, while ensuring the gain of the desired signal, minimize the total power, thereby suppressing the interference and noise power.

[0051] Based on the signal data received by multiple receiving antennas, obtain the covariance matrix R of the actual array received signal:

[0052]

[0053] Where X(k) is the received array signal, H represents the conjugate transpose, and K represents the data block length.

[0054] During the continuous signal processing, update R by superposition:

[0055]

[0056] Where n represents the number of superpositions, and X(n) represents the nth array received signal.

[0057] Based on the covariance matrix R, calculate the optimal weight vector as:

[0058] W opt =R -1 α(θ 0 )[α H (θ 0 )R -1 α(θ 0 )] -1 (7);

[0060] Where (-1) represents taking the inverse of the matrix, and α(θ 0 ) represents the steering vector of the desired signal.

[0061] The solution to the linearly constrained minimum variance (LCMV) is actually to solve the following constrained problem:

[0062]

[0063] Where P out represents the output power of the adaptive array, and C is a constant, generally taking C = 1.

[0064] E[|x(t)| 2 ] represents the power of the received signal, By optimizing W opt , so that the power of the received signal is minimized, that is, calculate W opt Minimize the function.

[0065] Applying the Lagrange multiplier method to equation (8) yields equation (7).

[0066] Solve the optimal weight vector to make the output power P out Minimum, can effectively suppress interference and noise.

[0067] In the process of solving the linear constrained minimum variance LCMV, matrix inversion operation is used. When the signal is a pure signal without interference and noise, the matrix often cannot be inverted, resulting in no calculation results. In practice, the signal-to-noise ratio must be at least less than 40dB. Due to the random independence of the noise, the matrix can be inverted to obtain the calculation results. In real systems, the signal-to-noise ratio is almost impossible to be greater than 40dB. Based on this, matrix inversion is feasible.

[0068] like Figure 1 As shown in the figure, in the aircraft-ground communication system, an omnidirectional antenna is used on the ground and an array antenna is used on the aircraft. The communication is carried out in a time-division manner. The time when the aircraft transmits signals to the ground, TDL, and the time when the aircraft receives signals from the ground, TUL, is time-division. The time when the aircraft transmits signals to the ground, TDL, is downlink, and the time when the ground transmits signals and the aircraft receives signals from the ground, is uplink. The uplink data includes the UL synchronization signal.

[0069] According to the signal transmission time TDL and reception time TUL of each array element on the aircraft, the search duration Tsearch is set for data sliding search. After the search duration, the calculation duration Tcal is set for calculating the searched data.

[0070] The aircraft receiving signal includes a local pilot signal, a received pilot signal and a received data signal.

[0071] To ensure that each slide of each sliding search contains uplink data, thereby ensuring that each slide has a synchronization signal, the search duration includes at least 2 receiving times and at least 1 transmitting time. In this application, the search duration includes 2 receiving times and 1 transmitting time as an example. Figure 2 shown.

[0072] During the search duration, the signal data time used for calculation should be as short as possible, and the useful signal data in the received signal should be excluded as much as possible. If the useful signal data is included, the calculation result will suppress the useful signal. Since during the aircraft transmission data period, the data received by the aircraft must not contain useful signals and only contains interference and noise, the aircraft received data during TDL downlink is used to calculate the linearly constrained minimum variance to achieve the suppression of the interference and noise power.

[0073] In the aircraft-ground communication system, initially, since the aircraft does not know its own location, the aircraft needs to perform angle search.

[0074] Assume that the aircraft is at a relatively long distance, and at this time the pitch angle β is close to 90 degrees. Therefore, the initial pitch angle β is set to 90 degrees during the search. 0 At this time, on the horizontal plane, a search is performed within the range of 0 to 360° at the set search angle interval keli. Then the total number of searches is: MAXsp = 360 / keli. The angle search index is sp, and the corresponding search angle is sp × keli°, where the range of sp is [1:MAXsp].

[0075] Each time a search is performed and each time there is a sliding correlation, the data on all array elements is collected to form a set of data corresponding to this search angle, including M * N data, which form a complex vector with a length of ANT = M * N. For each set of data, the covariance matrix R is calculated according to formula (5), the covariance matrix is updated when connecting the data according to formula (6), and the optimal weight vector W is calculated according to formulas (7)(8). opt and the steering vector α(θ 0 ) of the desired signal to obtain the optimal weight vector W of all array elements at all search angles. opt The data set W opt list[1:ANT][1:MAXsp].

[0076] At a certain search angle thindex × keli°, for each array element within each search duration, each time a sliding sample is taken, a correlation is performed once to obtain a set of discrete search data for this array element. Based on the search data of this array element, the covariance matrix R of this array element at this search angle and this search duration is calculated. i,q,sp and the optimal weight vector W opt(i,q,sp) .

[0077] As Figure 3 shown, first, the optimal weight vectors W on all array elements at the same search angle and within the same search duration Tsearch are calculated. opt(i,q,sp) Weighting is performed to obtain the first signal y1 sp (t):

[0078] y1 spy(t) = sum(conj(W opt(i,q,sp) (1:ANT)) × X(t, 1:ANT)) (9);

[0079] where W opt(i,q,sp) (1:ANT) represents the optimal weight vector of all array elements, X(t, 1:ANT) represents the data of all array elements at the same time, and the sum function is used for summation.

[0080] Synchronously correlate the locally received pilot signal Pilot_Locald within the reception time TUL with the first signal continuously during the search time to obtain the correlation peak point of the second signal y2 sp (t), and calculate the peak power point Peak sp at this search angle based on the correlation peak point of the second signal y2 sp , and the maximum signal-to-noise ratio SNRmax sp .

[0081] y2 sp (t) = sum(y1 sp (t:t + L_pilot - 1) × conj(P_Liot Local )) (10);

[0082] where L_pilot represents the length of the local pilot signal sequence, and P_Liot Local represents the local pilot signal. This equation means that at a certain search angle, the sum is obtained after conjugate correlation of all the first signals from time t to time t + the length of the local pilot signal sequence with the local pilot signal.

[0083] Find the maximum value of all the correlation peak points of the second signal within the same search duration at a certain search angle, and use it as the peak point Peak sp

[0084] Peak sp = max(y2 sp (t)) (11);

[0085] Calculate the conjugate correlation of all the first signals with the local pilot signal from time t to time t + the length of the local pilot signal sequence at a certain search angle, and use it as the third signal y1(t) sp :

[0086] y1(t) sp = y1(t:t + L_pilot - 1) × conj(P_Liot Local ) (12);

[0087] conj(P_LiotLocal ) represents calculating the complex number PLiot Local for its conjugate value.

[0088] Process all the third signals within the search duration, calculate the average value, then take the absolute value and square it to obtain the first data pws:

[0089] pws = (abs(mean(y1(t) sp ))) 2 (13);

[0090] mean(y1(t) sp ) represents calculating the average value of the array y1(t) sp ; abs represents the absolute value function.

[0091] Process all the third signals within the search duration, first take the absolute value and then square it, and then calculate the average value to obtain the second data pwall:

[0092] pwall = mean(abs(y1(t) sp )) 2 ) (14);

[0093] Subtract the second data from the first data to obtain the third data pwn.

[0094] pwn = pwall - pws (15);

[0095] Calculate the ratio of the first data to the third data to obtain the fourth data snr(t) at this search angle sp .

[0096] snr(t) sp = pws / pwn (16);

[0097] The maximum value among the fourth data within all search durations at this search angle is the maximum signal-to-noise ratio SNRmax at this search angle sp .

[0098] SNRmax sp = max(snr(t) sp ) (17);

[0099] In a specific embodiment of the present application, the local pilot signal sequence is a PN sequence, an M sequence [1, -1, 1,...].

[0100] Finally, traverse all search angles to obtain the peak points and maximum signal-to-noise ratios corresponding to all search angles.

[0101] Sort all the peak points to obtain the maximum peak point Peak_V and the point with the highest SNR. The angle corresponding to this point is the aircraft angle, and the local pilot is the known pilot.

[0102] [maxPeakV, maxpP] = MAX(y2 sp ) (18);

[0103] [SNRpmaxmax, maxpS] = MAX(SNRmax sp ) (19);

[0104] maxPeakV represents the peak complex vector signal, maxpP represents the index position where the peak point is located, SNRpmaxmax represents the maximum signal-to-noise ratio, and maxpS represents the index position where the maximum signal-to-noise ratio is located.

[0105] maxpP × keli° or maxpS × keli° represents the angle of the target aircraft.

[0106] According to subsequent simulations, it is more accurate to measure based on the maximum SNR. Therefore, maxpS × keli° is used as the final angle.

[0107] According to the maximum value index maxpS, calculate the weighting coefficient corresponding to the maximum peak point and the maximum signal-to-noise ratio point as the optimal weighting coefficient W opt O:

[0108] W opt O = W opt List[1:ANT][maxpS] (20);

[0109] According to W opt O perform spatial filtering on the ANT root array element antennas to obtain the D signal:

[0110] d = sum(x_ul(1:ANT, t) × conj(W opt O(1:ANT))) (21);

[0111] The interference in the signal d has been suppressed, and subsequent processing such as subsequent synchronous search and frequency offset measurement correction can be performed. At the same time, further determine the pilot data of the ANT root antenna according to the synchronization point for subsequent calculations.

[0112] The method of obtaining the azimuth by searching for the angle, as Figure 4 shown, includes the following steps:

[0113] S1. Start;

[0114] S2. Set the search angle interval Keli and calculate the maximum number of searches; calculate W through LCMV within the calculation time opt , and search for the peak point according to W opt within the search duration;

[0115] S3. Determine whether the search angle is completed. If so, go to S8; if not, proceed to the next step;

[0116] S4. Collect the received signal, obtain the steering vector α(θ 0 ) of the desired signal at the current angle, perform LCMV calculation, and obtain the weighted value W opt at this angle;

[0117] S5. According to the weighted value W opt at this angle, merge the data of the Ka root antennas of the received signal to obtain the first signal y1 sp (t) at this angle;

[0118] S6. The local pilot sequence slides and correlates within the set search duration Tsearch, records the peak power point Peak sp obtained within the current search duration, and calculates the signal-to-noise ratio SNR(sp) using the correlation information of the peak point;

[0119] S7. sp = sp + 1, update the search angle, and go to S3;

[0120] S8. Calculate the maximum value among the peak power points of all search angles and the maximum value among the signal-to-noise ratios, and obtain the corresponding weighted coefficient W opt O, that is, extract the optimal weighted value W opt O from the maximum value group;

[0121] S9. Use W opt O to perform weighted merging on the signals in the subsequent receiving time UL to obtain the D signal;

[0122] S10. Signal synchronization and frequency offset measurement and correction;

[0123] S11. According to the synchronization signal, extract the pilot part data of the ANT root array antennas at the synchronization point, correlate with the local pilot signal data, and obtain the final optimized weighted value Weightop; among them, the signal synchronization point can be found according to the previous relevant peak points.

[0124] S12. Merge the Ka root antennas into one channel to complete the subsequent signal equalization and demodulation processing;

[0125] S13. End.

[0126] In step S10, the SMI (Sample Matrix Inversion) sampling matrix inversion algorithm is adopted to process the sampling data, and the optimized weighted value Weightop is obtained.

[0127] The optimal weighted value W opt is calculated and then used for subsequent calculations after O.

[0128] After the subsequent received signals are weighted and summed, they are subjected to sliding correlation capture with the known sequence in the data segment. When the known sequence in the subsequent data segment is captured, the signal-to-noise ratio is estimated using the data of the known sequence and recorded.

[0129] Generally, the known sequence in the data segment is located at the front of each data segment as the leading header. Using the independent cross-correlation characteristics of multiple leading headers and the leading headers inserted in the data sequence, the timing error is initially estimated, and the interpolation loop is used to track the timing estimation error to obtain real-time adjustment of timing synchronization for sliding correlation capture. When the leading header is captured, the signal-to-noise ratio is estimated using the data of the leading header and recorded.

[0130] After traversing all search angles, the direction with the largest signal-to-noise ratio estimation value is taken as the azimuth angle of the searched aircraft.

[0131] In practice, there is a relatively large difference between the actual azimuth angle obtained by searching and the estimated azimuth angle, but this does not affect the demodulation of the uplink signal. When the aircraft-ground position is obtained based on the demodulated information, the true azimuth angle can be calculated.

[0132] In a specific embodiment of the present application, assuming that the uplink time TUL is 2 ms and the downlink time TDL is 8 ms, to ensure that there is a synchronization signal during each sliding, the search duration is set to 8 + 2 * 2 = 12 ms, and the calculation duration is 1 ms; then the search period is 12 ms + 1 ms = 13 ms.

[0133] The search angle interval is 10°, so the total number of searches for 360° is 360 / 10 = 36.

[0134] After 36 searches, the time used is 13 ms * 36 = 0.468 s.

[0135] Assuming that the desired signal direction is 20° and the interference signal direction is 70°, and the search is carried out at intervals of 10°. After 36 searches, the interference is the largest at 70°, and the measured SNR is the smallest, so it is determined that the interference direction is 70°. The SNR is the largest at 20°, and it is determined that 20° is the desired signal direction.

[0136] There are two ways to calculate the direction of the incoming wave, including determining based on the magnitude of the correlation peak power and determining by measuring the SNR value.

[0137] When determining the direction of arrival of the incoming wave according to the magnitude of the relevant peak power, the relevant peak power of the direction of arrival of the desired signal is not necessarily the highest, and the relevant peak power of the interference direction is not necessarily the lowest.

[0138] When determining the direction of arrival of the incoming wave by measuring the SNR value, it is possible to accurately estimate the direction of arrival of the interference signal and the direction of arrival of the desired signal according to the magnitude of the SNR.

[0139] A terminal device for initial angle search in a time-division system of an array antenna under strong interference provided by an embodiment of the present invention. The terminal device of this embodiment includes: a processor, a memory, and a computer program stored in the memory and executable on the processor, such as an arithmetic program. When the processor executes the computer program, the method described in this application is implemented.

[0140] Exemplarily, the computer program can be divided into one or more modules / units. The one or more modules / units are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions. These instruction segments are used to describe the execution process of the computer program in the terminal device for initial angle search in the time-division system of the array antenna under strong interference. For example, the computer program can be divided into multiple modules, and the specific functions of each module are as follows:

[0141] 1. A data processing module, used to obtain sliding data during the search duration;

[0142] 2. A calculation module, used to calculate the covariance, maximum power point, etc. of the data;

[0143] 3. A subsequent data processing module, used to process subsequent signals based on the optimal weighting value.

[0144] The terminal device for initial angle search in the time-division system of the array antenna under strong interference can be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The terminal device for initial angle search in the time-division system of the array antenna under strong interference may include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the above examples are only examples of the terminal device for initial angle search in the time-division system of the array antenna under strong interference, and do not constitute a limitation on the terminal device for initial angle search in the time-division system of the array antenna under strong interference. It may include more or fewer components than those shown in the figure, or combine some components, or different components. For example, the terminal device for initial angle search in the time-division system of the array antenna under strong interference may further include input / output devices, network access devices, a bus, etc.

[0145] The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The processor is the control center of the initial angle search terminal device of the array antenna time-division system under strong interference, and connects all parts of the initial angle search terminal device of the array antenna time-division system under strong interference through various interfaces and lines.

[0146] The memory can be used to store the computer program and / or module. By running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory, the processor realizes various functions of the initial angle search terminal device of the array antenna time-division system under strong interference. The memory mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, phone book, etc.), etc. In addition, the memory can include high-speed random access memory, and can also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage devices.

[0147] The embodiments of this specific implementation manner are all preferred embodiments of the present invention, and do not limit the protection scope of the present invention accordingly. Therefore, all equivalent changes made according to the structure, shape, and principle of the present invention should be covered within the protection scope of the present invention.

Claims

1. An initial angle search method for a time-division system of an array antenna under strong interference. The array antenna includes M*N array elements located in the XOY plane. It is characterized in that a search angle interval and a search duration are set. The local pilot signal is received at the time of the transmitted signal within the search duration, and the covariance matrix and the optimal weight vector of the first local signal received by each array element are calculated. The optimal weight vector signals on all array elements within the same search angle and the same search duration are weighted and combined to obtain the peak power point and the maximum signal-to-noise ratio at this search duration and this search angle. All search angles are traversed to obtain the maximum peak point and the highest signal-to-noise ratio point. The corresponding search angle is the initial angle, and the corresponding optimal weight vector is the best weighting coefficient. The subsequent received signals are spatially filtered with the best weighting coefficient. After signal synchronization and frequency offset correction, the pilot part data of all array element antennas is correlated with the local pilot signal data to obtain the final optimized weighting value, and signal equalization and demodulation processing are performed. Within the same search angle and the same search duration, the data collected on all array elements form a complex vector with a length of ANT = M * N, and the covariance matrix R and the optimal weight vector W are calculated for each set of data opt , obtaining the optimal weight vector data set, weighting all the optimal weight vector data to obtain the first signal; synchronously correlating the local pilot signal received within the reception time with the first signal continuously during the search time to obtain the second signal at the correlation peak point. Based on the second signal at the correlation peak point, calculate the peak power point, the maximum signal-to-noise ratio, and the steering vector α(θ 0 ) at this search angle; Based on the covariance matrix R, the optimal weight vector is calculated as: W opt = R -1 α(θ 0 )[α H (θ 0 )R -1 α(θ 0 )] -1 ; (-1) represents the inverse operation on the matrix, and α(θ 0 ) represents the steering vector of the desired signal.

2. The initial angle search method for a time-division system of an array antenna under strong interference according to claim 1, It is characterized in that it further includes a calculation duration, and the calculation duration and the search duration are arranged at intervals to form a search period. The search duration includes at least two received signal durations and at least one transmitted signal duration to ensure that there is a synchronization signal each time when sliding correlation is performed within the search duration.

3. The initial angle search method for a time-division system of an array antenna under strong interference according to claim 1, It is characterized in that the maximum value of all the second signals of the relevant peak points under the same search angle and within the same search duration is used as the peak power point at this search angle and this search duration.

4. The initial angle search method for a time-division system of an array antenna under strong interference according to claim 1, It is characterized in that under the same search angle, within the time period of the local pilot signal sequence length, the conjugate correlation is performed between all the first signals and the local pilot signal to obtain a third signal. The third signals in all time periods are processed, the average value is obtained, then the absolute value is taken and finally squared to obtain a first data. Then, for the third signals in all time periods, the absolute value is taken first and then squared, and then the average value is obtained to obtain a second data. The second data is subtracted from the first data to obtain a third data. The ratio of the first data to the third data is obtained to obtain the fourth data at this search angle. The maximum value among the fourth data in all search durations at this search angle is the maximum signal-to-noise ratio at this search angle.

5. The initial angle search method for a time-division system of an array antenna under strong interference according to claim 1, It is characterized in that all search angles are traversed to obtain the peak point data set and the maximum signal-to-noise ratio data set corresponding to all search angles. The maximum value in the peak point data set is taken as the maximum peak point, and the maximum value in the maximum signal-to-noise ratio data set is taken as the highest signal-to-noise ratio.

6. The initial angle search method for a time-division system of an array antenna under strong interference according to claim 1, It is characterized in that Calculate the weighting coefficients corresponding to the maximum peak point and the maximum signal-to-noise ratio point as the optimal weighting coefficient, and perform spatial domain filtering on the ANT root array element antenna according to the optimal weighting coefficient to obtain a signal, which is used for subsequent synchronization search, frequency offset measurement and correction processing. Determine the pilot data of the ANT root antenna according to the synchronization point for subsequent calculations.

7. The initial angle search method for the array antenna time division system under strong interference according to claim 6, wherein, According to the optimal weighting coefficient, weight and combine the signals at the subsequent reception time to obtain a signal, and perform synchronization and frequency offset measurement correction on the subsequent signals; according to the synchronization signal, extract the pilot part data of the ANT root array element antenna at the synchronization point and correlate it with the local pilot signal data to obtain the final optimized weighting value Weightop; combine the Ka root antennas into one channel to complete the subsequent signal equalization and demodulation processing.

8. The initial angle search method for the array antenna time division system under strong interference according to claim 1, wherein, The method for searching the azimuth angle includes the following steps: S1. Start; S2. Set the search angle interval Keli and calculate the maximum number of searches; calculate W through LCMV within the calculation time opt , and search for the peak point according to W within the search duration opt ; S3. Determine whether the search angle is completed. If so, go to S8. If not, go to the next step; S4. Collect the received signal, and according to the currently cycled angle, obtain the steering vector α(θ 0 ) of the desired signal at this angle, perform LCMV calculation, and obtain the weighted value W opt ; S5. According to the weighted value W of this angle opt , combine the data of Ka root antennas of the received signal to obtain the first signal y1 sp (t) of this angle; S6. Slide and correlate the local pilot sequence within the set search duration Tsearch, and record the peak power point Peak within the duration obtained at the current search duration. sp , calculate the signal-to-noise ratio using the correlation information of the peak point; S7. sp = sp + 1, update the search angle, and go to S3; S8. Calculate the maximum value among the peak power points of all search angles and the maximum value of the signal-to-noise ratio, and obtain the corresponding weighting coefficient W opt O, that is, extract the optimal weighting value W from the maximum value group opt O; S9. Adopt W opt O to perform weighted combination on the signals at the subsequent UL moment to obtain signals; S10. Perform synchronization and frequency offset measurement correction on the subsequent signals; S11. According to the synchronization signal, extract the pilot part data of the ANT root array element antenna at the synchronization point and correlate it with the local pilot signal data to obtain the final optimized weighting value Weightop; S12. Combine the Ka root antennas into one channel to complete the subsequent signal equalization and demodulation processing; S13. End.

9. An initial angle search terminal for the array antenna time division system under strong interference, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, it implements the method according to any one of claims 1-8.

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