TCN and ATC integrated signal identification method

Abstract

The invention belongs to the technical field of signal processing, and particularly relates to a TCN and ATC integrated signal identification method, which comprises the following steps of: 1, carrying out band-pass pre-filtering on a received radio frequency signal, and extracting the pre-filtered data into two paths; 2, DFT processing and spectrum analysis processing are carried out on the A-path data to obtain a spectrum distribution diagram of the signals, and frequency domain sorting filtering is carried out on the signals with TCN and ATC distribution; carrying out delay processing on the B-path data; 3, performing digital band-pass filtering on the data of the path B according to the information of the spectrum distribution diagram obtained by the path A; 4, performing coherent demodulation to obtain an I-path signal and a Q-path signal; 5, delaying the I-path signal and the Q-path signal respectively to obtain an I'path signal and a Q 'path signal; the method comprises the steps of (1) obtaining I-path signals and Q-path signals, (2) obtaining I-path signals and Q-path signals, (3) obtaining I-path signals and Q-path signals, (4) obtaining I-path signals and Q-path signals, (5) obtaining I-path signals and Q-path signals, (6) carrying out signal superposition on the I-path signals and the Q-path signals to obtain sigma signals, (7) carrying out pulse matching filtering on the sigma signals, identifying signal types, entering (8) if the signals are ATC signals, and entering (9) if the signals are TCN signals, (8) carrying out mode identification on the ATC signals,

Description

Technical Field

[0001] The present invention belongs to the technical field of signal processing, and in particular relates to a TCN and ATC integrated signal recognition method. Background Art

[0002] With the rapid development of electronic information technology, traditional airborne discrete equipment is gradually developing in the direction of functional integration. In the military field, in order to enhance combat capabilities, combat platforms tend to develop in the direction of miniaturization and diversification, striving to equip a variety of electronic information equipment on the smallest possible platform, which leads to increased electromagnetic interference between different systems. The use of functional integration is an effective way to reduce interference between systems.

[0003] In view of the fact that airborne TACAN and ATC currently still use separate functional implementation methods, by sorting out the working frequency bands, implementation methods and processing logic of TACAN and ATC, it can be found that the traditional RF physical integration can be further integrated through the unified processing of functional algorithms. On the basis of traditional RF integration, further full use can be made of multi-dimensional resource information such as physics, space, and electromagnetic spectrum to further improve combat technical indicators. Summary of the invention

[0004] The purpose of the present invention is to propose a design method for integrated TACAN and ATC signal recognition, in particular, to integrate the functions of traditional TACAN and ATC signal detection and recognition by direct radio frequency acquisition, and to achieve the sorting and recognition of TACAN and ATC signals by adopting a set of waveform algorithms.

[0005] The technical solution of the present invention:

[0006] A TCN and ATC integrated signal recognition method, the steps are as follows:

[0007] Step 1: bandpass pre-filtering the received RF signal, and extracting the pre-filtered data into two paths;

[0008] Step 2: Perform DFT processing on the data of channel A to obtain a complex domain spectrum diagram, calculate the spectrum data, perform spectrum analysis processing based on the spectrum data to obtain the spectrum distribution diagram of the signal, perform frequency domain sorting and filtering on the signals distributed by TCN and ATC to obtain the signals within the bandwidth of TCN and ATC; perform delay processing on the data of channel B;

[0009] Step 3: Based on the information of the spectrum distribution diagram obtained from channel A, digital bandpass filtering is performed on the data from channel B;

[0010] Step 4: Perform coherent demodulation to obtain I-channel signal and Q-channel signal;

[0011] Step 5: Delay the I-path signal and the Q-path signal respectively to obtain the I'-path signal and the Q'-path signal;

[0012] Step 6: Superimpose the I'-path signal and the Q'-path signal to obtain a Σ signal;

[0013] Step 7: Perform pulse matching filtering on the Σ signal to identify the signal type. If it is an ATC signal, proceed to step 8; if it is a TCN signal, proceed to step 9;

[0014] Step 8: Perform pattern recognition on ATC signals;

[0015] Step 9: Identify and decode the TCN signal.

[0016] Further, in step 2, the DFT processing process is as follows:

[0017]

[0018] in, x(n) is the input digital signal,

[0019] X(k) is the peak value of each frequency point, which can effectively calculate the position of the current frequency point

[0020] Furthermore, in step 3, the digital bandpass filter uses an FIR filter, and the basic function is:

[0021]

[0022] Among them, x(n) is the input signal, h(n) is the matched filter template, and y(n) is the filtered spectrum data.

[0023] Furthermore, in step five, the signal delay process is to perform N-beat delays preferentially based on empirical parameters; N is not greater than the shortest length of an ATC or TCN pulse data.

[0024] Furthermore, in step six, the Σ signal calculation formula is as follows:

[0025] Σ=I'(n)+Q'(n).

[0026] Further, in step seven, the pulse matching filter calculation formula is as follows:

[0027]

[0028] Where N is the length of the signal digital domain, calculated based on the template of each signal;

[0029] p(n)=∑P1(n-T1)+P2(n-T2)+P3(n-T3)+P5(n-T5)

[0030] Among them, T1, T2, T3, and T5 are the positions of the signal pulses respectively;

[0031] Further, in step eight, the signal inquiry mode is identified according to the ATC signal template, and the process is as follows:

[0032] The input signal pulse sequence is s(n), the template of the A-mode interrogation signal is ATC_A(n), the template of the C-mode interrogation signal is ATC_C(n), the template of the A / C-mode interrogation signal is ATC_A / C(n), and the template of the S-mode interrogation signal is ATC_S(n);

[0033] Use different templates to perform sliding interpolation calculation on the input signal pulse sequence to obtain the Δ signal. The formula is as follows:

[0034] Δ=∑s(Tn)-ATC_X(n)

[0035] ATC_X(n) is ATC_A(n) or ATC_C(n) or ATC_A / C(n) or ATC_S(n);

[0036] It is determined whether the Δ signal is similar to the query signal of the corresponding template. If so, it is the pattern query signal corresponding to the template.

[0037] Furthermore, the TCN signal recognition and decoding process is as follows:

[0038] The Gaussian pulse template based on TACAN signal is used for identification; the pulse decoding pair is used for judgment;

[0039] Pulse decoding performs difference processing on the received signal, and performs pulse accumulation to obtain relevant information by difference. The pulse decoding signal simultaneously obtains the ranging pulse and the reference pulse.

[0040] Pulse decoding pair

[0041]

[0042] p(n) is the matching pulse signal, N is the cumulative number of pulses, N=12. By judging the Ω signal, the following conclusions can be drawn:

[0043] Ω<Ω0: the signal is an amplitude envelope signal, Ω>Ω1: the signal is a reference pulse and a ranging echo signal, where Ω1>Ω0, and the values ​​of the two are based on the empirical values ​​of the database;

[0044] By pulse decoding the template matching signal, an envelope signal consisting of several pulse pairs is obtained, and the spectrum of the envelope of the received pulse stream is detected to assist in determining the presence of the TACAN signal;

[0045] Compare the signal amplitude within a pulse width time after the pulse arrival time, and take the maximum amplitude as the peak point of the pulse. These peak points constitute the envelope curve;

[0046] The signal pulse after peak detection is a composite signal composed of 135Hz and 35Hz. The composite signal can be demodulated by the coherent signals of 135Hz and 35Hz respectively to obtain the envelope pulse signal of the two signals, and then obtain the phase signal;

[0047] The signal obtained by mutual coherent demodulation has multiple spectral components, and the multiple spectral components are filtered to obtain a cosine signal waveform diagram of the signal;

[0048] Normalize the amplitude, x(n)>S, x(n)=s0

[0049] For a pulse pair, the rule for x(n) to identify the main reference pulse is:

[0050] In X mode, the main reference pulse group consists of 24 pulses, and these pulses form a pulse pair in pairs, with a total of 12 pulse pairs. The interval between the two pulses in each pulse pair is 12±0.1μs, and the interval between each two adjacent pulse pairs is 30±0.1μs.

[0051] In Y mode, the main reference pulse group consists of 13 pulses, and the interval between adjacent pulses is 30±0.1μs;

[0052] Through this pulse matching criterion, the main reference pulse and its pattern are determined, and the pulse time of the main reference pulse is obtained as t 主 ;

[0053] For a pulse pair, the rule for x(n) to identify the auxiliary reference pulse is:

[0054] In X mode, the auxiliary reference pulse group consists of 12 pulses, which form a pulse pair in pairs like the main reference, for a total of 6 pulse pairs. The interval between the two pulses in each pulse pair is 12±0.1μs, and the interval between each two adjacent pulse pairs is 24±0.1μs.

[0055] In the Y mode, the auxiliary reference pulse group also consists of 13 pulses, but the interval between adjacent pulses is 15±0.1μs;

[0056] Through this pulse matching criterion, the auxiliary reference pulse and its pattern can be determined; and the pulse time of the main reference pulse is obtained as t 辅 ;

[0057] For a pulse pair, the rule for x(n) to identify the ranging pulse is:

[0058] The distance reply pulse consists of two pulses, and the pulse interval is 12±0.1μs in X mode and 30±0.1μs in Y mode. When the ground base station receives the inquiry signal sent by the airborne equipment, it will transmit a reply pulse after a specified delay. The delay time is 50±0.1μs in X mode and 56±0.1μs in Y mode. During the delay period, the ground base station does not transmit other signals, but because the priority of the distance reply pulse is only higher than the filling pulse, it will first transmit other types of pulses and then calculate the reply delay. In this way, the arrival time t of the distance reply pulse is calculated. 测距 ;

[0059] For a pulse pair, the rule for x(n) to identify the pulse is:

[0060] The identification pulse consists of two pulses, the pulse interval of which is 12±0.1μs in X mode and 30±0.1μs in Y mode; the identification pulse is synchronized with the azimuth reference pulse group, and there should be an equalizing pulse with the same code as the identification pulse at 100±10μs afterwards; the identification signal is obtained by sampling the identification pulse for several seconds;

[0061] The rough bearing measurement is based on the main reference pulse time t in S10.2.1.2.1. 主 The information of the 0 phase of the azimuth coarse pulse is used to obtain the corresponding time difference:

[0062] Δt 主 =min{t 主 -t n},(t 主 -t n )>0

[0063] Calculate the relative time Δt 主 Convert to the corresponding azimuth value:

[0064]

[0065] By auxiliary quasi-pulse time t 主 The information of the 0 phase of the azimuth coarse pulse is used to obtain the corresponding time difference:

[0066] Δt 辅 =min{t 辅 -t n},(t 辅 -t n )>0

[0067] Relative time Δt 辅 Convert to the corresponding azimuth value:

[0068]

[0069] By integrating the received TACAN and ATC signals, the signal type can be effectively identified based on prior knowledge and template data, and the characteristic distribution within the signal can be determined. Integrated recognition processing can effectively solve the shortcomings of traditional recognition of each waveform separately.

[0070] Beneficial effects of the present invention:

[0071] The present invention can effectively improve the integrated application capability of TACAN and ATC signals in the military field, effectively identify navigation and recognition signals in an increasingly complex electromagnetic environment, thereby enhancing the adaptability of the platform and improving the overall combat effectiveness of the platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 : The overall processing flow chart of the present invention;

[0073] Figure 2 : Spectrum calculation flow chart;

[0074] Figure 3 : Frequency point pre-sorting information diagram;

[0075] Figure 4 : FIR filter;

[0076] Figure 5 :matlab FDATool tool;

[0077] Figure 6 :Schematic diagram of coherent demodulation;

[0078] Figure 7 : A, C inquiry signal format;

[0079] Figure 8 : S mode inquiry signal format;

[0080] Fig. 9 : TACAN pulse pair signal format;

[0081] Fig.10 : Schematic diagram of the waveform after peak detection. DETAILED DESCRIPTION

[0082] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0083] The present invention relates to a TACAN and ATC integrated signal recognition design method, and in particular to a method of performing functional integration processing on traditional TACAN and ATC signal detection and recognition by means of radio frequency direct sampling, and realizing the sorting and recognition of TACAN and ATC signals by adopting a set of waveform algorithms.

[0084] The specific implementation process of the present invention is as follows Figure 1 shown.

[0085] S1. Broadband RF signal decomposition based on RF direct sampling

[0086] In this method, the main working frequency band is 960Mhz~1.3GHz. Therefore, before the sampling signal starts, in order to ensure the rapid access of the effective signal, the RF signal is pre-filtered, and the frequency below 960MHZ and above 1.3GHz is filtered out by using a bandpass filter. In the selection of sampling rate, the signal retention characteristics in Nyquist sampling theorem are taken into consideration. It can be seen that the input signal is a continuous signal with limited bandwidth. Therefore, the sampling frequency ω s >2ω m , where ω s =2π / T, T is the sampling period.

[0087] Therefore, in this solution, the sampling rate is selected as 3.0Msps.

[0088] After sampling the signal, according to the signal processing characteristics, the input tape-out signal is extracted, and the extracted signal enters two paths for processing. Here, the extraction coefficient does not violate Shannon's sampling theorem. Enter S2 and S1.1 steps respectively.

[0089] S1.1, frequency selective filter

[0090] A wide-sampling signal is a signal that contains all characteristic information within a bandwidth of 960Mhz to 1.3GHz. However, for TCN and ATC interrogation signals, their characteristics are a single frequency point and strong signal correlation. Therefore, the signal can be estimated from the frequency domain by performing DFT processing on the sampled signal.

[0091]

[0092] in, x(n) is the input digital signal,

[0093] X(k) is the peak value of each frequency point, which can effectively calculate the position of the current frequency point

[0094] Here, we can get the spectrum diagram in the complex domain, and through the operation of the real and imaginary parts, we can get the estimation of the spectrum data. s, record the position of the value of X(k) f1,f2,f3,... Here, X s is the prior information. The calculation process is as follows Figure 2 .

[0095] Therefore, the set of spectrum data is: f(n) = {f1, f2, f3...}. f(n) is the collection of spectrum.

[0096] S1.2, frequency sorting filter

[0097] By estimating the statistical peak value, the peak value of the spectrum signal is selected according to the prior information, that is, f>f max , f max is the prior information. Multiple frequency point information can be obtained, and the count here is f(n) = {f1, f2, f3...}. The allocation information is as follows Figure 3 .

[0098] Here, the spectrum information of f'(n) is stored and input to S3 for digital down-conversion and filtering.

[0099] S2. Delayed processing

[0100] The first signal is delayed according to the processing period, and the delay period is determined by the time delay of the processing of S1.1 to S1.2.

[0101] S3, digital bandpass filtering

[0102] Digital bandpass filtering is performed based on the spectrum in f(n), and the signal is pre-sorted and filtered. According to prior information, the ATC interrogation signal is a point frequency signal with a frequency of 1030Mhz. If f(n) contains this spectrum information, the filter is set to 8Mhz. The rest can be the frequency point information of TCN, and the filter is set to 3MHz. Here, the intermediate frequency point of the filter is set to the center frequency point of the signal to be demodulated in f(n), and the signal after frequency conversion is x(n).

[0103] Here, the digital bandpass filter uses a FIR filter, and the basic function is:

[0104]

[0105] In the formula, the tap coefficients h(n) of the N filters are multiplied by the N sampled data x(n) respectively, and the accumulated sum is the output result. The basic structure diagram of the FIR filter is as follows: Figure 4 .

[0106] Here, in this method, the fdatool tool in matlab can be used to pre-select N. Figure 5 .

[0107] S4, coherent demodulation (digital down conversion)

[0108] The x(n) signal is converted to baseband through digital down-conversion technology according to the f(n) spectrum information. Here, the digital down-conversion adopts a one-time down-conversion method, mixing the digital signal through the positive and residual signals of the two channels, and then extracting the signal through the extraction filter, thereby realizing the down-conversion of the signal and obtaining the I channel signal and the Q channel signal respectively. Figure 6 shown.

[0109] Right now

[0110] I(n)=x(n)·cos(ωn)

[0111] Q(n)=x(n)·sin(ωn)

[0112] The I-channel signal and the Q-channel signal are complex signals with spectrum replication. To ensure the effectiveness of signal out-of-band suppression, they can be processed by low-order low-pass filters. FIR low-pass filters are also selected.

[0113] In this way, we obtain a functional signal with a clean spectrum and single information.

[0114] S5.1, S5.2, S6.1, S6.2: Signal delay processing

[0115] In order to maximize the reception of the signal power spectrum, considering that both ATC and TCN signals are point-frequency signals, the signal power spectrum can be obtained by delaying and adding the I and Q signals. Here, the signal delay phase is π / 4 phase.

[0116] S7, signal superposition, phase estimation

[0117] The delay-aligned I-path signal and Q-path signal are added together, that is:

[0118] Σ=I'(n)+Q'(n)

[0119] Δ=I'(n) / F(n)

[0120] In this way, the envelope and the difference signal of the received signal can be obtained respectively through the Σ and Δ signals. In the method described in this article, only the Σ signal is used for processing.

[0121] S8, pulse matching filter

[0122] Considering the signal correlation, the ATC signal has a fixed pulse characteristic and the TCN signal has a fixed filling pulse characteristic. Since the pulse model here does not undergo pulse shaping processing, the time domain characteristics of the pulse signal are not obvious. The method described in this article can perform correlation signal analysis on the pulse signal through the matched filtering method, thereby identifying whether it is a TCN signal or an ATC signal.

[0123] The algorithms for matched filtering in the time domain are:

[0124]

[0125] Where N is the length of the signal in the digital domain, p(n) is the template of the known signal, and the matched filter. T is the delay period. Here, it is calculated based on the template of each signal.

[0126] In this way, two signals with related characteristics can obtain higher energy values, and it can be determined whether they are ATC signals, TCN signals or other signals.

[0127] ATC and TCN signals have different characteristics regarding the choice of matched filters.

[0128] Among them, the interrogation signal format of the ATC interrogation signal is as follows: Figure 7 and Figure 8 .

[0129] According to the secondary radar interrogation signal standard, A and C modes are determined by the pulse position information of P1 pulse and P3 pulse, among which P2 pulse is a sidelobe suppression pulse. S mode determines the arrival of the signal by the pulse position of P1 and P2 pulses.

[0130] Therefore, the matched filter for the ATC signal can be expressed as:

[0131] p(n)=∑P1(n-T1)+P2(n-T2)+P3(n-T3)+P5(n-T5)

[0132] Among them, T1, T2, T3, and T5 are the positions of the signal pulses respectively.

[0133] As for the TCN signal, it is known from the TCN standard that the characteristics of the pulses of the TCN signal are inconsistent depending on the mode (X, Y).

[0134] According to the standard requirements of TCN, the TCN signal can be identified by matching calculations of two pulse pairs and matching correlation peaks, just like the ATC waveform. Here, the TCN signal is divided into X mode and Y mode. It should be noted that the width of the reference pulse signal in X mode and Y mode is the same, both 3.5+1us, but the spacing between pulses is different in different modes. In the X working mode, the pulse pair spacing of the main reference pulse group is 30±0.1μs, and the spacing between two pulses in the same pulse pair is 12±0.1μs. A group of main reference pulse groups contains a total of 12 Gaussian pulse pairs; in the Y working mode, the main reference pulse group consists of 13 Gaussian single pulses with a pulse spacing of 30±0.1μs. The pulse group repetition frequency of the main reference pulse group is 15±0.3Hz.

[0135] S9, Signal Identification

[0136] Through the matching and identification of the signal modules in S8, it can be known that the ATC and TCN signals contain 5 modes and 2 modes respectively, that is, the specific signal can be identified by the symbol characteristics of the pulse.

[0137] If the ATC and TCN signals cannot be matched, it proves that they are not navigation and surveillance signals within the frequency band. Then it is necessary to further distinguish the signal characteristics to determine whether they are communication signals or other signals.

[0138] Through signal recognition, the ATC signal and TACAN signal can be identified and information extracted through S10.1 and S10.2 respectively.

[0139] S10.1 Interrogation signal extraction and recognition

[0140] If the identified signal is an ATC signal, the signal interrogation mode can be identified based on the ATC signal template, because in the interrogation signal, there are multipath reflections, etc., which require sidelobe suppression through the P2 pulse. Therefore, the identification method of the interrogation signal can be calculated and processed through the cross-correlation of the template.

[0141] The interrogation signal includes an A-mode interrogation, a C-mode interrogation, an A / C-mode interrogation, and an S-mode interrogation.

[0142] Here, the input signal pulse sequence is x(n)s(n).

[0143] The template of the A-mode interrogation signal is counted as ATC_A(n)

[0144] The template of the C-mode interrogation signal is counted as ATC_C(n)

[0145] The template of the A / C mode interrogation signal is denoted as ATC_A / C(n)

[0146] The template of the S mode interrogation signal is denoted as ATC_S(n)

[0147] The signal can be identified by calculating the sliding difference. Then the pulse characteristics in the template signal are calculated by statistics to determine whether it is an interrogation signal.

[0148] For example, for the A-mode interrogation signal, the sliding difference algorithm is:

[0149] Δ=∑x(Tn)-ATC_A(n)

[0150] Here T is the sliding window.

[0151] By analyzing the statistical characteristics of Δ, we can determine what kind of interrogation signal it is.

[0152] S10.1.1A Mode Interrogation Signal Recognition

[0153] When Δ and A mode interrogation signal Δ A If they are similar, it can be determined to be an A-mode interrogation signal.

[0154] S10.1.2 Mode C interrogation signal recognition

[0155] When Δ and C-mode interrogation signal Δ C If they are similar, it can be determined to be a C-mode interrogation signal.

[0156] S10.1.3 Mode A / C interrogation signal recognition

[0157] When Δ and A / C mode inquiry signal Δ A / C If they are similar, it can be determined to be an A / C mode inquiry signal.

[0158] S10.1.4 Mode S interrogation signal recognition

[0159] When Δ and S-mode interrogation signal Δ S If the two signals are similar, it can be determined to be an S-mode interrogation signal. Here, it should be noted that, since the S-mode interrogation signal carries coded information, the extraction of the interrogation signal requires further BPSK demodulation of the signal. This is not the method of the present invention.

[0160] S10.2 Gaussian pulse decoding

[0161] If the identified signal is a TACAN signal, a Gaussian pulse template based on the TACAN signal can be used for identification.

[0162] The TACAN system uses a pulse code modulation signal. The pulse form uses a Gaussian pulse signal, which is encoded in the form of pulse pairs. The interval time between pulse pairs and the interval time within pulse pairs are used to express different information. The mathematical expression of the Gaussian pulse signal is:

[0163]

[0164] The c in the formula reflects the steepness of the pulse, and 2ln2c is the width at half the peak. The basic pulse unit of TACAN is in the form of Fig. 9 shown.

[0165] TCN signals are pre-processed through Gaussian modulation of the signal, such as ranging, direction finding, and identification tone signals.

[0166] S10.2.1 TACAN arrival signal recognition

[0167] Signal identification is to ensure that the signal of the current TACAN station matches the navigation direction of the own aircraft signal. If the matched signal is consistent with the received signal, it proves that the signal is the signal of the navigation station, otherwise, it proves that it is not a TCN signal.

[0168] The signal of signal recognition is judged by pulse decoding. Pulse decoding mainly performs difference processing on the received signal, and performs pulse accumulation to obtain relevant information by difference.

[0169] At the same time, the pulse decoding signal simultaneously obtains the ranging pulse and the reference pulse, so that certain data information can be obtained for ranging and direction finding.

[0170] Pulse decoding pair

[0171]

[0172] Here, if p(n) is the matching pulse signal, N is the cumulative number of pulses, here, according to the number of main and auxiliary reference pulse pairs required for TACAN direction finding, we can get N=12. By judging the Ω signal, we can draw the following conclusions:

[0173] Ω<Ω0: The signal is an amplitude envelope signal

[0174] Ω>Ω1: signal reference pulse and ranging echo signal

[0175] Among them, Ω1>Ω0, and the values ​​of the two are based on the empirical values ​​of the database.

[0176] S10.2.1.1. Peak inspection

[0177] By matching the template-matched signal with pulse decoding, an envelope signal consisting of several pulse pairs can be obtained. The TACAN baseband signal is composed of Gaussian pulses and envelopes. The envelope is a modulated signal composed of 15 Hz and 135 Hz sine waves. The frequency spectrum of the envelope of the received pulse stream can be detected to assist in determining the presence of the TACAN signal. The TACAN baseband signal is formed by amplitude modulating Gaussian pulses with a composite field of 15 Hz and 135 Hz. The envelope is composed of the apex of the pulse, so the envelope curve can be constructed by determining the peak value of the pulse. The method for measuring the pulse peak is to compare the signal amplitude within a period of time (a pulse width time) after the pulse arrival time, and take the maximum amplitude as the peak point of the pulse. These peak points constitute the envelope curve, such as Fig.10 shown.

[0178] S10.2.1.1.1. Mutual Interference Demodulation

[0179] The signal pulse after peak detection is a composite signal composed of 135Hz and 35Hz. In this way, the composite signal can be demodulated by the coherent signals of 135Hz and 35Hz respectively, and the envelope pulse signal of the two signals can be obtained to obtain the phase signal. The demodulation equation is:

[0180] f(n)=x(n)·cos(f0*n)

[0181] Among them, x(n) is the signal envelope, and the cosine function is the demodulation envelope. In this way, the signals that can be obtained are the signal envelope of 135 Hz and the signal envelope of 35 Hz. Here, because the synthesized signal has a complex signal frequency characteristic, it is possible to include a frequency-multiplied signal of 135+35 Hz.

[0182] S10.2.1.1.1.1, 15 Hz filter

[0183] Since the signal obtained by mutual coherence demodulation has multiple spectral components, it is necessary to filter the multiple spectral components. Here, a low-pass filter can be used, and the filtering bandwidth is the spectral component of the signal. In this way, the cosine signal waveform of the signal can be obtained. The position of π / 2 can be obtained.

[0184] S10.2.1.1.1.2 135 Hz filter

[0185] Since the signal obtained by mutual coherence demodulation has multiple spectral components, it is necessary to filter the multiple spectral components. Here, a low-pass filter can be used, and the filtering bandwidth is the spectral component of the signal. In this way, the cosine signal waveform of the signal can be obtained. The position of π / 2 can be obtained.

[0186] S10.2.1.2, Limiting, Pulse Identification

[0187] Here, the main constraint is the amplitude inconsistency, because the signal after pulse decoding and signal recognition has the characteristic of inconsistent amplitude. Therefore, in order to ensure the convenience of subsequent calculations, the amplitude can be normalized.

[0188] x(n)>S,x(n)=s0

[0189] In this way, the consistency of amplitude can be ensured.

[0190] Furthermore, by examining the characteristics of the pulse, according to the standard, it can be determined whether it is a main reference pulse, an auxiliary reference pulse, a distance measurement pulse or an identification sound pulse.

[0191] S10.2.1.2.1. Main reference pulse identification and decoding

[0192] For a pulse pair, the rule for x(n) to identify the main reference pulse is:

[0193] In X mode, the main reference pulse group consists of 24 pulses, and these pulses form a pulse pair in pairs, with a total of 12 pulse pairs. The interval between two pulses in each pulse pair is 12±0.1μs, and the interval between every two adjacent pulse pairs is 30±0.1μs.

[0194] In Y mode, the main reference pulse group consists of 13 pulses, and the interval between adjacent pulses is 30±0.1μs.

[0195] Through this pulse matching criterion, the main reference pulse and its pattern can be determined, and the pulse time of the main reference pulse is obtained as t 主 .

[0196] S10.2.1.2.2. Auxiliary reference pulse identification and decoding

[0197] For a pulse pair, the rule for x(n) to identify the auxiliary reference pulse is:

[0198] In X mode, the auxiliary reference pulse group consists of 12 pulses, which form a pulse pair in pairs like the main reference, for a total of 6 pulse pairs. The interval between the two pulses in each pulse pair is 12±0.1μs, and the interval between each two adjacent pulse pairs is 24±0.1μs.

[0199] In the Y mode, the auxiliary reference pulse group also consists of 13 pulses, but the interval between adjacent pulses is 15±0.1μs.

[0200] Through this pulse matching criterion, the auxiliary reference pulse and its pattern can be determined. And the pulse time of the main reference pulse is obtained as t 辅 .

[0201] S10.2.1.2.3. Ranging pulse decoding and identification

[0202] For a pulse pair, the rule for x(n) to identify the ranging pulse is:

[0203] The distance reply pulse consists of 2 pulses, with a pulse interval of 12±0.1μs in X mode and 30±0.1μs in Y mode. When the ground base station receives the inquiry signal from the airborne equipment, it will transmit a reply pulse after a specified delay. The delay time is 50±0.1μs in X mode and 56±0.1μs in Y mode. During the delay period, the ground base station does not transmit other signals, but since the priority of the distance reply pulse is only higher than the filling pulse, it will transmit other types of pulses first and then calculate the reply delay.

[0204] In this way, the arrival time t of the distance reply pulse can be calculated 测距 .

[0205] S10.2.1.2.4. Identification pulse decoding and identification

[0206] For a pulse pair, the rule for x(n) to identify the pulse is:

[0207] The identification pulse consists of two pulses, and the pulse interval is 12±0.1μs in X mode and 30±0.1μs in Y mode. The identification pulse is synchronized with the azimuth reference pulse group, and there should be an equalizing pulse with the same code as the identification pulse at 100±10μs. The identification signal is obtained by sampling the identification pulse for several seconds.

[0208] S10.2.1.1.1.1.1. Rough measurement of orientation

[0209] The rough bearing measurement is based on the main reference pulse time t in S10.2.1.2.1. 主 The information of the 0 phase of the azimuth coarse pulse is used to obtain the corresponding time difference:

[0210] Δt 主 =min{t 主 -t n},(t 主 -t n )>0

[0211] In this way, the relative time Δt can be calculated 主 The corresponding azimuth value can be converted:

[0212]

[0213] S10.2.1.1.1.2.1 Precision measurement of orientation

[0214] The azimuth precision is determined by the auxiliary quasi-pulse time t in S10.2.1.2.1. 主 The information of the 0 phase of the azimuth coarse pulse is used to obtain the corresponding time difference:

[0215] Δt 辅 =min{t 辅 -t n},(t 辅 -t n )>0

[0216] In this way, the relative time Δt can be calculated 辅 The corresponding azimuth value can be converted:

[0217]

[0218] The above is only a specific embodiment of the present invention, and the present invention is described in detail. The unexplained part is a conventional technology. However, the protection scope of the present invention is not limited to this. Any changes or substitutions that can be easily thought of by any technician familiar with the technical field within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. The protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A TCN and ATC integrated signal recognition method, characterized in that: Here are the steps: Step 1: bandpass pre-filtering the received RF signal, and extracting the pre-filtered data into two paths; Step 2: Perform DFT processing on the data of channel A to obtain a complex domain spectrum diagram, calculate the spectrum data, perform spectrum analysis processing based on the spectrum data to obtain the spectrum distribution diagram of the signal, perform frequency domain sorting and filtering on the signals distributed by TCN and ATC to obtain the signals within the bandwidth of TCN and ATC; perform delay processing on the data of channel B; Step 3: Based on the information of the spectrum distribution diagram obtained from channel A, digital bandpass filtering is performed on the data from channel B; Step 4: Perform coherent demodulation to obtain I-channel signal and Q-channel signal; Step 5: Delay the I-path signal and the Q-path signal respectively to obtain the I'-path signal and the Q'-path signal; Step 6: Superimpose the I'-path signal and the Q'-path signal to obtain a Σ signal; Step 7: Perform pulse matching filtering on the Σ signal to identify the signal type. If it is an ATC signal, proceed to step 8; if it is a TCN signal, proceed to step 9; Step 8: Perform pattern recognition on ATC signals; Step 9: Identify and decode the TCN signal.

2. The method according to claim 1, characterized in that: In step 2, the DFT processing process is as follows: in, x(n) is the input digital signal, X(k) is the peak value of each frequency point, which can effectively calculate the position of the current frequency point.

3. The method according to claim 2, characterized in that: In step 3, the digital bandpass filter uses an FIR filter, and the basic function is: Among them, x(n) is the input signal, h(n) is the matched filter template, and y(n) is the filtered spectrum data.

4. The method according to claim 3, characterized in that: In step 5, the signal delay process is to perform N-beat delays based on empirical parameters; N is not greater than the shortest length of an ATC or TCN pulse data.

5. The method according to claim 4, characterized in that: In step six, the Σ signal calculation formula is as follows: Σ=I'(n)+Q'(n).

6. The method according to claim 5, characterized in that: In step 7, the pulse matching filter calculation formula is as follows: Where N is the length of the signal digital domain, calculated based on the template of each signal; p(n)=∑P1(n-T1)+P2(n-T2)+P3(n-T3)+P5(n-T5) Among them, T1, T2, T3, and T5 are the positions of the signal pulses respectively.

7. The method according to claim 6, characterized in that: In step eight, the signal interrogation mode is identified according to the ATC signal template, and the process is as follows: The input signal pulse sequence is s(n), the template of the A-mode interrogation signal is ATC_A(n), the template of the C-mode interrogation signal is ATC_C(n), the template of the A / C-mode interrogation signal is ATC_A / C(n), and the template of the S-mode interrogation signal is ATC_S(n); Use different templates to perform sliding interpolation calculation on the input signal pulse sequence to obtain the Δ signal. The formula is as follows: Δ=∑s(Tn)-ATC_X(n) ATC_X(n) is ATC_A(n) or ATC_C(n) or ATC_A / C(n) or ATC_S(n); It is determined whether the Δ signal is similar to the query signal of the corresponding template. If so, it is the pattern query signal corresponding to the template.

8. The method according to claim 7, characterized in that: The TCN signal recognition and decoding process is as follows: The Gaussian pulse template based on TACAN signal is used for identification; the pulse decoding pair is used for judgment; Pulse decoding performs difference processing on the received signal, performs pulse accumulation, and obtains relevant information by difference. The pulse decoding signal simultaneously obtains the ranging pulse and the reference pulse; Pulse decoding pair p(n) is the matching pulse signal, N is the cumulative number of pulses, N=12. By judging the Ω signal, the following conclusions can be drawn: Ω<Ω0: the signal is an amplitude envelope signal, Ω>Ω1: the signal is a reference pulse and a ranging echo signal, where Ω1>Ω0, and the values ​​of the two are based on the empirical values ​​of the database; By pulse decoding the template matching signal, an envelope signal consisting of several pulse pairs is obtained, and the spectrum of the envelope of the received pulse stream is detected to assist in determining the presence of the TACAN signal; Compare the signal amplitude within a pulse width time after the pulse arrival time, and take the maximum amplitude as the peak point of the pulse. These peak points constitute the envelope curve; The signal pulse after peak detection is a composite signal composed of 135Hz and 35Hz. The composite signal can be demodulated by the coherent signals of 135Hz and 35Hz respectively to obtain the envelope pulse signal of the two signals, and then obtain the phase signal; The signal obtained by mutual interference demodulation has multiple spectrum components, and the multiple spectrum components are filtered to obtain the cosine signal waveform of the signal; Normalize the amplitude, x(n)>S, x(n)=s0 For a pulse pair, the rule for x(n) to identify the main reference pulse is: In X mode, the main reference pulse group consists of 24 pulses, and these pulses form a pulse pair in pairs, with a total of 12 pulse pairs. The interval between the two pulses in each pulse pair is 12±0.1μs, and the interval between each two adjacent pulse pairs is 30±0.1μs. In Y mode, the main reference pulse group consists of 13 pulses, and the interval between adjacent pulses is 30±0.1μs; Through this pulse matching criterion, the main reference pulse and its pattern are determined, and the pulse time of the main reference pulse is obtained as t 主 ; For a pulse pair, the rule for x(n) to identify the auxiliary reference pulse is: In X mode, the auxiliary reference pulse group consists of 12 pulses, which form a pulse pair in pairs like the main reference, for a total of 6 pulse pairs. The interval between the two pulses in each pulse pair is 12±0.1μs, and the interval between each two adjacent pulse pairs is 24±0.1μs. In the Y mode, the auxiliary reference pulse group also consists of 13 pulses, but the interval between adjacent pulses is 15±0.1μs; Through this pulse matching criterion, the auxiliary reference pulse and its pattern can be determined; And, the pulse time of the main reference pulse is t 辅 ; For a pulse pair, the rule for x(n) to identify the ranging pulse is: The distance reply pulse consists of two pulses, and the pulse interval is 12±0.1μs in X mode and 30±0.1μs in Y mode. When the ground base station receives the inquiry signal sent by the airborne equipment, it will transmit a reply pulse after a specified delay. The delay time is 50±0.1μs in X mode and 56±0.1μs in Y mode. During the delay period, the ground base station does not transmit other signals, but because the priority of the distance reply pulse is only higher than the filling pulse, it will first transmit other types of pulses and then calculate the reply delay. In this way, the arrival time t of the distance reply pulse is calculated. 测距 ; For a pulse pair, the rule for x(n) to identify the pulse is: The identification pulse consists of 2 pulses, and the pulse interval is 12±0.1μs in X mode and 30±0.1μs in Y mode; The identification pulse is synchronized with the azimuth reference pulse group, and there should be an equalized pulse with the same code as the identification pulse at 100±10μs afterwards; the identification signal is obtained by sampling the identification pulse for several seconds; The rough bearing measurement is based on the main reference pulse time t in S10.2.1.2.

1. 主 The information of the 0 phase of the azimuth coarse pulse is used to obtain the corresponding time difference: Δt 主 =min{t 主 -t n },(t 主 -t n )>0 Calculate the relative time Δt 主 Convert to the corresponding azimuth value: By auxiliary quasi-pulse time t 主 The information of the 0 phase of the azimuth coarse pulse is used to obtain the corresponding time difference: Δt 辅 =min{t 辅 -t n },(t 辅 -t n )>0 Relative time Δt 辅 Convert to the corresponding azimuth value:

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