CN109975771B - Broadband digital channelization method based on signal third-order phase difference - Google Patents
Broadband digital channelization method based on signal third-order phase difference Download PDFInfo
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- G01—MEASURING; TESTING
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Abstract
The invention relates to a broadband digital channelization method based on signal third-order phase difference. By utilizing the digital channelization design of multiple phase differential detection and adopting differential detection, the signal detection threshold is normalized, so that the detection of a large instantaneous dynamic signal is realized, the subsequent phase refinement processing of the signal is facilitated, and the intra-pulse analysis of the signal is realized. The difference can realize the identification of the precise frequency measurement and phase coding signals for the signals. Therefore, the problem that the multichannel digital receiver is difficult to realize the self-adaptability of the threshold under the condition of large signal dynamic range is solved.
Description
Technical Field
The invention belongs to the technical field of radar countermeasure, and particularly relates to the technical field of signal detection and digital channelized receivers.
Background
The role of broadband reconnaissance receivers in electronic countermeasures is paramount. With the high-speed development of digital signal processing technology and corresponding device level, digital reconnaissance receivers are receiving more and more attention due to the advantages of small equipment quantity, flexible algorithm, easy expansion of functions and the like. In modern battlefields, the signal environment is dense and complex, the instantaneous bandwidth of a narrow-band radar signal is generally in the order of several MHz, and the instantaneous bandwidth of an ultra-wideband radar signal is more than several hundred MHz or even 1GHz, so that higher requirements are also provided for a wideband reconnaissance receiver, and the instantaneous bandwidth of the receiver is usually required to at least cover the instantaneous bandwidth of the radar signal so as to obtain complete signal spectrum information. Digital channelized receivers employ a digital filter bank to divide the instantaneous bandwidth coverage into a number of sub-bands, each referred to as a channel. And then detecting and measuring the output result of each channel, and finally obtaining the signal analysis result of the corresponding channel through threshold judgment, such as carrier frequency, arrival time, pulse width and the like.
In general, in a digital receiver, an amplitude detection method is generally adopted to detect a signal, and then a parameter measurement is performed on the signal according to a detection result. While this approach generally requires a higher signal-to-noise ratio and signal amplitude, the conventional approach is to increase the sensitivity of the receiving system by compressing the dynamic range of the receiving system. This is clearly not appropriate for wideband large instantaneous dynamic range receivers, where the strong signal does not disturb the weak signal appreciably, making it difficult to select an amplitude detection threshold for detecting the strong and weak signals. The digital receiver adopts signal three-order differential detection to normalize a signal detection threshold, is convenient for detecting large instantaneous dynamic signals, and can realize subsequent phase fine processing of the signals and intra-pulse analysis of the signals.
Disclosure of Invention
The current channelized receiving technology generally adopts an amplitude detection method to implement envelope detection on a signal, so as to implement measurement on the pulse width of the signal. When the dynamic range of a signal is large, that is, the range of pulse amplitude variation of the signal is wide, if effective detection of the signal is to be realized and the response of a false signal is to be avoided, an automatic threshold adjustment method is generally adopted, and for a multi-channel digital receiver, it is complicated to simultaneously realize the self-adaptation of the threshold. Under large transient dynamics, the strong signal may not interfere appreciably with the weak signal, making it difficult to select an amplitude detection threshold for detecting the strong and weak signals. The digital channelized design utilizing multiple-phase differential detection is provided by utilizing the characteristics of signal phases, and the digital receiver adopts differential detection to normalize a signal detection threshold, is convenient for detecting signals with large instantaneous dynamics, and is convenient for performing subsequent phase fine processing on the signals and realizing intra-pulse analysis on the signals.
For the convenience of describing the present invention, the following terms are first defined:
The ADC is an analog-to-digital converter, which is a device that converts an analog signal into a digital signal;
The FFT is a fast Fourier transform, is a fast algorithm of discrete Fourier transform, and converts a time domain signal into a frequency domain form, and a discrete signal x (n) passes through a formula
Obtaining a discrete time Fourier transform of X (n) X (e) jw ) (ii) a The IFFT is the inverse of the FFT, converting the frequency domain form of the signal to a time domain representation;
X(e jw ) By the formula
Obtaining X (e) jw ) The inverse fourier transform x (n);
the discrete signal x (n) is processed by formula
Obtaining a z-transform X (z) of X (n),
x (z) is represented by the formula
Obtaining an inverse z-transform X (n) of X (z);
The FIR filter is a finite-length single-bit impulse response filter, also called a non-recursive filter, and is the most basic element in a digital signal processing system, and can ensure any amplitude-frequency characteristic and simultaneously have strict linear phase-frequency characteristic, and simultaneously, the unit sampling response of the FIR filter is finite-length, so that the filter is a stable system;
the FIR filter group is a group of filters, which can realize subband decomposition of signals, and then perform various processing or transmission on each subband according to requirements;
Convolution is a mathematical operation and is widely applied in the field of signal processing;
let f (x), g (x) be two integrable functions, and integrate to obtain the convolution result of two signals:
The analytic signal is M paths of signals obtained after the original signal is subjected to time delay extraction and then is converted into an M signal, and then the M signals are convoluted with a filter multiphase structure to generate M paths of filtering output, the FFT of M points is continuously completed to complete the frequency shift operation of channelization filtering, and the M signals are converted into a time domain again. Each signal is a complex signal that can be expressed as:
y(n)＝u(n)+j*v(n)＝|y(n)|e jθ(n) (2)
the instantaneous phase θ (n) of y (n) is:
definition 6, PDW
PDW is a pulse description word consisting of TOA, pulse width, signal frequency, signal amplitude, etc. Where TOA is the pulse arrival time. And the data output by the polyphase filter bank is time domain data, the data output by the filter bank is subjected to phase difference detection, then threshold detection output is carried out, and finally the PDW stream is obtained through a PDW coding circuit. Wherein the PDW formation process is shown in FIG. 1;
the PDW coding circuit has the input of signal amplitude, channel number, clock, differential detection result and output of PDW stream, and the circuit consists of a front edge generating circuit, a back edge generating circuit, a pulse width counter, a TOA counter and a latch, and the connection mode is shown in the figure;
definition 7, phase differential detection
Characteristics of the digital channelized signal and noise. After digital channelization, the noise can be represented as:
n(t)＝n c (t)cosω c t-n s (t)sinω c t (9)
in the formula n c (t) and n s (t) are referred to as in-phase and quadrature components, respectively.
The synthesized signal of the sinusoidal signal plus the narrow-band gaussian noise can be expressed as:
from equation (12), it can be demonstrated that random phase
The distribution is related to the signal-to-noise ratio in the channel, and the phase is determined when the signal-to-noise ratio is 0
Changing to a uniform distribution, when the signal-to-noise ratio is much greater than 1,
mainly concentrated around the signal phase, i.e. under the condition that a certain SNR is met,
is mainly affected by the signal;
for fixed frequency signals
First order difference of
Is a constant after a second order difference
The linear frequency modulation signal is subjected to second-order differential processing to obtain the frequency modulation slope of the signal
Is a constant, so it is necessary to
Can be obtained after three-order differential processing
Therefore, in order to adapt to the conventional signal and the linear frequency modulation signal, a third-order phase difference detection mode is adopted for detection. The method is different from the general amplitude detection mode, the adopted detection signal is not higher than the threshold but lower than the threshold, because no matter the linear frequency modulation signal, the conventional signal or the phase coding signal (except for the step point) is zero after being subjected to multi-order differential processing, which is obviously different from noise and can be detected.
Step 1: initialization parameters
The initialization parameters include: radiation source intermediate frequency signals s (t), f s Is the sampling rate of the ADC; the method comprises the following steps of (1) counting the number M of multi-phase filtering digital channels, the order L of a filter, the number N of coefficients of multi-phase filtering and a preset differential threshold value T;
step 2: signal sampling
ADC sampling is carried out on the radiation source intermediate frequency signal s (t) in the step 1, wherein t represents the total signal time length, and the sampling frequency is f s Obtaining a sampling signal s (n), n =0,1,2, \8230;, t/f s ；
And step 3: signal polyphase representation and decimation
And (3) outputting the sampling signal s (n) obtained in the step (2) in parallel by M paths, wherein the M paths of signals respectively pass through the time delay units with the time delay of 0, 1.. And M-1 units to obtain M paths of signals s n, s n-1.. And s (n-M + 1). Then, for the M signals s n, s n-1,.., s n-M +1. Using the formula s r n = s M × n-r, r =0,1,2, M-1 is calculated to yield M times the decimated signal s 0 n,s 1 n,...,s M-1 n；
And 4, step 4: filter bank design
First, an FIR filter is defined as h (N) with a length of N. The FIR filter arrangement is divided into M groups, each group representing a channel, and the r-th channel can be represented as h (r + nM), where M is the number of channelizations, and N/M = Q, Q is a positive integer, 1 ≦ r ≦ N. Using formulas
The z-transform result E of the r channel h (r + nM) is calculated r (z) and the filter z-transform result can be expressed as:
next, E is r (z) inverse z-transform to obtain E r (k)；
The M paths of signals s obtained in the step 3 are processed 0 n,s 1 n,...,s M-1 n is respectively equal to E r (k) R =0, 1.. Multidot.m-1 is convolved to obtain M channels of signals I r (n)，r＝0,1,...,M-1；
And 5: frequency shift conversion
M paths of signals I to be generated r (n) FFT to obtain a frequency spectrum Y r R =0,1,. Multidot., M-1. In the frequency domain by formula
Obtaining the true center frequency f of the signal r Wherein f is c For measuring frequency, f s Is the sampling frequency and r is the number of the channel on which the signal is located. True center frequency f r Corresponding signal spectrum is
And 6: signal output after filter bank processing
The M paths of signal frequency spectrums obtained in the step 5
IFFT conversion is carried out to obtain M paths of signals y r (n)，r＝0,1,...,M-1；
And 7: third order phase difference
The M paths of signals y obtained in the step 6 are processed r (n) representing y by complex signal form r (n)|e jθ(n) R =0, 1.. Multidot.m-1, resulting in M channels of signal y r (n) an instantaneous phase θ (n);
next, the M-channel signals y obtained in step 6 are processed r (n) representing y by complex signal form r (n)＝u r (n)+j×v r (n) obtaining a signal y r Real part u of (n) r (n) and imaginary part v r (n) of (a). According to the signal y r Real part u of (n) r (n) and imaginary part v r (n)，
Calculating an instantaneous phase theta' (n) without ambiguity after ambiguity resolving operation through an arc tangent phase;
then, the first order difference sequence phi is obtained by calculation of the formula (15) 1 (n)
Calculating to obtain a first-order difference sequence phi 1 (n)
φ 1 (n) by the formula
Calculating to obtain a third-order difference sequence phi 3 (n) third order difference phi for common single frequency signals, chirp signals, phase encoded signals, etc 3 (n) are all 0. In addition, when strong and weak signals with different amplitudes exist at the same time, because the three-order difference of the signals is zero, the normalized threshold detection of the signals with different amplitudes and different types of signals can be realized; and 8: third order differential threshold detection
The common channelized receiver uses the amplitude of a signal as a threshold for detection, and when strong and weak signals arrive at the same time, the fixed threshold adopted in the selection of the threshold obviously cannot meet the requirement of detecting large and small signals at the same time. The third-order differential envelope of the channelized signal is compared with a preset threshold value T, so that the detection threshold normalization of the strong and weak signals is realized, and the dynamic adaptability of the channelized receiver to the simultaneously arriving signals is improved. When the third-order difference of the signal is lower than a threshold T, judging that the signal exists, and when the third-order difference of the signal is higher than the threshold T, judging that no signal exists, and measuring the pulse arrival time TOA of the signal according to the time corresponding to the difference threshold; comparing the third-order differential envelope of the channelized signal with a preset threshold value T, realizing the detection threshold normalization of the strong and weak signals, and solving the problem that the detection threshold cannot be adapted to the strong and weak signals when the traditional amplitude threshold cannot simultaneously exist;
and step 9: generating PDW
And obtaining a PDW stream through a PDW coding circuit according to the difference threshold detection result, wherein the PDW stream has a channel number, a difference detection TOA result, an amplitude value output by envelope detection and a pulse width.
The invention has the innovative points that the phase characteristics of signals are fully utilized, a digital channelization design utilizing multiple-phase differential detection is provided, and the differential detection is adopted to normalize the signal detection threshold, so that the detection of signals with large instantaneous dynamics is realized, the subsequent phase fine processing of the signals is facilitated, and the intra-pulse analysis of the signals is realized. Therefore, the problem that the multichannel digital receiver is difficult to realize the self-adaptability of the threshold under the condition of large signal dynamic range is solved. In addition, the difference can realize the identification of the precise frequency measurement and phase coding signals for the signals. Simulation shows that interference of strong signals can cause certain influence on frequency measurement of weak signals, and detection of the weak signals is difficult to realize by adopting common amplitude detection and FFT frequency measurement methods; and the detection of weak signals in the simultaneously arriving signals is feasible by adopting a phase difference detection and frequency estimation method.
The phase differential detection has the following advantages: the detection threshold is normalized, and the influence of unbalanced signal amplitude is avoided. Instantaneous frequency estimation can be performed on the signals simultaneously. The modulated form of the signal can be preliminarily identified through multiple differences. And the channel discrimination after channelization is convenient.
Drawings
Figure 1 is a block diagram of a PDW formation process,
figure 2 is a simulation of the phase difference results obtained with an input single frequency signal,
figure 3 is a simulation of the phase difference results from inputting a continuous frequency modulated signal,
figure 4 is a simulation of the phase difference results from the input BPSK signal,
fig. 5 is a simulation diagram of the results of the third-order phase difference corresponding to the simultaneous presence of strong and weak signals.
Detailed Description
The feasibility of the scheme is verified mainly by adopting a simulation experiment method, and all steps and conclusions are verified to be correct on the MATLAB R2010 a. The specific implementation steps are as follows:
step 1: initialization parameters
The sampling rate of the ADC is 1.0GHz, the number of channels in simulation M =64, the order of a filter L =384, and the number of coefficients of each path of polyphase filtering N =6;
input signal s (t) divided into three times
The first input s (t) being a single frequency signal
A is the signal amplitude, f 0 Is the carrier frequency of the signal and,
is the initial phase of the signal and is the initial phase of the signal,
the second input signal s (t) being a chirp signal
A is the signal amplitude, tau pulse interval time, f 0 The frequency of the carrier of the signal, the mu modulation frequency,
the third input signal s (t) is BPSK signal s (t) = Acos (2 π f) 0 t+φ n ) A is the signal amplitude, f 0 Is the carrier frequency of the signal phi n Is the signal phase.
As can be seen from fig. 2, 3 and 4, for the common single-frequency signal, chirp signal and phase-encoded signal, the original waveform, first-order difference, second-order difference and third-order difference of the signal are consistent with the theoretical analysis, and the result of the third-order difference is all approximately zero. In fig. 5, the difference result of two signals with different amplitudes is obtained, for the conventional detection, because the amplitude difference of the two signals is large, a certain problem exists when the detection threshold is set to be too large or too small, the small signal cannot be detected when the threshold is too large, and a large amount of false alarm signals can be generated when the threshold is too low. As can be seen from the processing results in fig. 5, after the third-order differential processing, the differential results of the positions of the two groups of signals are both zero, so that the normalized threshold detection of the signals of different types and different amplitudes is realized.
Claims (1)
1. The broadband digital channelization method based on the signal third-order phase difference is characterized by comprising the following steps of:
step 1: initialization parameters
The initialization parameters include: intermediate frequency signal s (t) of radiation source, t representing total signal time length, f s Is the sampling rate of the ADC; the method comprises the following steps of (1) counting the number M of multi-phase filtering digital channels, the order L of a filter, the number N of coefficients of multi-phase filtering and a preset differential threshold value T;
step 2: signal sampling
ADC sampling is carried out on the radiation source intermediate frequency signal s (t) in the step 1, and the sampling frequency is f s Obtaining a sampled signal s (n), n =0,1,2, \ 8230;, t/f s ；
And step 3: signal polyphase representation and decimation
Outputting the sampling signal s (n) obtained in the step 2 in parallel to M paths, wherein the M paths of signals are delayed by 0,1 and M-1 units through a delayer to obtain M paths of signals s n, s n-1, s (n-M + 1), and then, for the M paths of signals s n, s n-1, 1 r n = s M × n-r, r =0,1,2,.., M-1, calculated to yield M times the decimated signal s 0 n,s 1 n,...,s M-1 n；
And 4, step 4: filter bank design
Defining the FIR filter as h (N) with a length of N, arranging the FIR filters into M groups, each group representing one channel, then the r-th channel is represented as h (r + nM) and N/M = Q, Q is a positive integer, 1 ≦ r ≦ N, using the formula
The result E of the z-transform of the r-th channel h (r + nM) is calculated r (z) then E r (z) inverse z-transform to obtain E r (k) R is the channel number, k =0, 1.., Q-1;
the M paths of signals s obtained in the step 3 are processed 0 n,s 1 n,...,s M-1 n, each with E r (k) R =0, 1.. M-1 is convolved to obtain M channels of signals I r (n)，r＝0,1,...,M-1；
And 5: frequency shift conversion
M paths of signals I to be generated r (n) FFT to obtain a frequency spectrum Y r R =0, 1.., M-1, in the frequency domain by the formula
Obtaining the true center frequency f of the signal r Wherein f is c For measuring frequency, f s Is the sampling frequency, r is the channel number of the signal;
step 6: signal output after filter bank processing
The M paths of signal frequency spectrums Y obtained in the step 5 are processed r R =0, 1.. And M-1, and performing IFFT to obtain M paths of signals y r (n)，r＝0,1,...,M-1；
And 7: third order phase difference
The M paths of signals y obtained in the step 6 are processed r (n) representing | y by the number of poles of the complex signal r (n)|e jθ (n), r =0,1,. And M-1, resulting in M signals y r (n) an instantaneous phase θ (n);
then, the M paths of signals y obtained in the step 6 are used r (n) representation of y in planar complex signal form r (n)＝u r (n)+j×v r (n) obtaining the messageNumber y r Real part u of (n) r (n) and imaginary part v r (n) from the signal y r Real part u of (n) r (n) and imaginary part v r (n), calculating an instantaneous phase theta' (n) without ambiguity after ambiguity resolving operation through an arc tangent phase;
the first order difference sequence phi is obtained by calculation through the formula (15) 1 (n)，
φ 1 (n) calculating to obtain a third-order difference sequence phi through a formula (15) 3 (n)；
And step 8: third order differential threshold detection
Comparing the third-order difference envelope of the channelized signal with a preset threshold value T, judging that the signal exists when the third-order difference of the signal is lower than the threshold T, judging that no signal exists when the third-order difference of the signal is higher than the threshold T, and measuring the time of arrival (TOA) of the pulse of the signal according to the time corresponding to the difference threshold;
and step 9: generating PDW
And obtaining a PDW stream through a PDW coding circuit according to the difference threshold detection result, wherein the PDW stream has a channel number, the difference detection TOA result, an amplitude value output by envelope detection and a pulse width.
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| CN106453178A (en) * | 2016-11-06 | 2017-02-22 | 中国电子科技集团公司第十研究所 | Satellite-based AIS signal intercept and demodulation method |
| CN107634768A (en) * | 2017-09-11 | 2018-01-26 | 哈尔滨工程大学 | A kind of MWC compression sampling wideband digital receiver PDW forming methods based on FPGA |
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| US6085077A (en) * | 1997-01-21 | 2000-07-04 | Us Air Force | Hardware efficient digital channelized receiver |
| CN106453178A (en) * | 2016-11-06 | 2017-02-22 | 中国电子科技集团公司第十研究所 | Satellite-based AIS signal intercept and demodulation method |
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