CN117233462A - Photon-assisted distributed compressive sampling system and implementation method thereof - Google Patents
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Abstract
The invention discloses a photon-assisted distributed compression sampling system, which comprises a multi-wavelength light source, a first wavelength division multiplexer in a far-end node, a first electro-optic modulator, a second wavelength division multiplexer, an erbium-doped fiber amplifier (EDFA), a wavelength division demultiplexer in a central site, a second electro-optic modulator, a photoelectric detector, a low-pass filter, a sampler, a joint reconstruction calculation module, an antenna connected with the first electro-optic modulator in the far-end node and a pseudo-random sequence generator connected with the second electro-optic modulator in the central site. Aiming at the monitoring requirement of the distributed broadband signal spectrum, the invention uses the optical carrier radio frequency mode to pull back a plurality of remote node signals to the central station for processing, and simultaneously adopts the photon compression sampling technology and the combined reconstruction algorithm to realize the efficient compression sampling of the remote node signal spectrum at the central station.
Description
Technical Field
The invention belongs to the technical field of microwave photon signal processing, and particularly relates to a photon-assisted distributed compression sampling system and an implementation method thereof.
Background
Digital signal processing technology has the advantages of flexibility, high speed, high precision, strong anti-interference capability and the like, and has become the mainstream technology in the field of signal processing. Analog-to-digital converter Analog-to-digital converters and ADCs construct a bridge that represents and processes natural signals with digital signals. In recent years, analog-to-digital conversion technology is continuously developed, and the sampling rate is continuously improved, but for some systems with instantaneous bandwidth larger than 10GHz, such as ultra-wideband communication and radar countermeasure systems, the existing ADC cannot meet the requirements. The compressive sampling theory was proposed by d.l. donoho et al in 2006, which theory holds that: if the signal is sparse, or can be sparsely represented in a domain, it can reconstruct the sparse signal at a sampling rate well below the nyquist rate. 2009 j.a. Tropp et al proposed using a random demodulator model to implement compressive sampling, frequency sparse signals could be reconstructed by a structure of random mixing, filtering and low-speed sampling. However, compressed sampling systems based on random demodulator models are limited by the bandwidth and performance of the electrical random signal and electrical mixing devices. Photonics technology and devices have the characteristics of low loss, large bandwidth, strong anti-interference capability, parallel processing and the like, and attract wide research interests. J.M. Nichols et al in 2011 utilized photon links to implement mixing functions in compressive sampling, improving the bandwidth of compressive sampling systems.
On the other hand, baron et al put forward a distributed compressive sampling theory in order to make full use of the correlation between signals and inside signals. In the theory, the system is provided with a plurality of distributed nodes, signals received by the nodes meet a joint sparse model, a sending end performs independent compressive sampling on each node, a receiving end performs joint reconstruction through a distributed compressive sampling algorithm by utilizing the correlation of the signals, and compared with a scene of independently reconstructing each sparse signal by the receiving end, the distributed compressive sampling requires fewer measured values and has higher reconstruction accuracy. Baron et al also proposed three joint sparse models for different scenarios, called JSM-1, JSM-2 and JSM-3, respectively. The common part of JSM-1, JSM-2 and JSM-3 requires that the spectral sparse signal frequency bin positions and amplitudes are all the same. Later, sundman et al proposed a hybrid support set model in which only the frequency points of the common part are the same, the amplitudes can be different, and the hybrid support set model has more universal and practical applications. Distributed compressive sampling systems have unique advantages, and are continuously researched, but only the simulation and experiment are performed by using electronic devices, and the working bandwidth and the frequency monitoring range are constrained by the performance of the electric domain.
Aiming at the technical problems, the improvement is needed. The following is described with respect to the application of the signal to conform to the hybrid support set model.
Disclosure of Invention
Based on the defects existing in the prior art, the invention provides a photon-assisted distributed compression sampling system and an implementation method thereof, and aims at the monitoring requirement of a distributed broadband signal spectrum, remote node signals are pulled back to a central station for processing by utilizing an optical carrier radio frequency mode, meanwhile, the central station adopts a photon compression sampling technology and a joint reconstruction algorithm to realize efficient compression sampling of the remote node signal spectrum, the photon-assisted distributed compression sampling system has the advantages of ultra-high bandwidth of the photon compression sampling technology and optical fiber distributed long-distance transmission, and is expected to realize long-distance, multi-node and wide-coverage space electromagnetic spectrum monitoring.
In order to solve the technical problems, the technical scheme of the invention is as follows:
a photon-assisted distributed compressed sampling system comprises a first wavelength division multiplexer, a first electro-optic modulator, an antenna, a second wavelength division multiplexer, an erbium-doped fiber amplifier (EDFA), a multi-wavelength light source in a central site, a wavelength division demultiplexer, a second electro-optic modulator, a pseudo-random sequence generator, a photoelectric detector, a low-pass filter, a sampler and a joint reconstruction calculation module.
A realization method of a photon-assisted distributed compressive sampling system comprises the following steps:
the multi-wavelength light source provides J wavelengths of continuous light with wavelength lambda 1 ，λ 2 The right of the left of the right of the left of the up to lambda J The multi-wavelength optical carrier is transmitted clockwise through a single-mode optical fiber to a first remote node where the wavelength is lambda 1 Is extracted through the first wavelength division multiplexer, while other optical carriers pass directly. The sparse signal of the frequency to be detected received by the antenna is modulated to an optical carrier lambda through a first electro-optic modulator 1 And then the modulated optical signal and other optical wavelengths are combined by a second wavelength division multiplexer and then continue to be transmitted on the optical fiber. In an optical fiber transmission line, an erbium-doped fiber amplifier EDFA is added to compensate for the loss of line optical power. Similarly, in the J (J represents the wavelength sequence number, J is less than or equal to J far-end nodes), the sparse signal of the frequency to be detected is modulated to an optical carrier lambda through a first electro-optic modulator j Up to the J-th remote node. The multi-wavelength optical carrier carrying J-path radio frequency information is transmitted back to the central station by the optical fiber. First, the optical carrier wave is decomposed into J paths of optical carrier waves through a wave-splitting multiplexer, and each path of optical carrier wave carrying radio frequency information respectively enters a second electro-optical modulator to be mixed with J different pseudo-random sequences generated by a pseudo-random sequence generator. The mixed signals of each path are converted into electric signals through a photoelectric detector, and then a J-group compressed sampling measurement value sequence y is obtained through a low-pass filter and a sampler j [n]. Will y j [n]And sending the signals to a signal joint reconstruction calculation module, and jointly recovering the to-be-detected frequency sparse signals of J remote nodes through a distributed compressive sampling reconstruction algorithm.
As a preferred scheme of the invention, J frequency sparse signals received by J remote nodes in the implementation method of the photon-assisted distributed compressive sampling system are frequency domain sparse signals and meet a mixed support set model so as to represent the correlation between the signals and the signals.
As a preferable scheme of the invention, in the implementation method of the photon-assisted distributed compressive sampling system, the repetition rate of the pseudo-random binary sequence sent by the pseudo-random sequence generator is required to be greater than or equal to the Nyquist frequency of the J-path frequency sparse signal, so that the signal obtained by mixing the frequency sparse signal and the pseudo-random sequence can keep all information of the original sparse signal.
The invention has the following characteristics and beneficial effects:
1 in the invention, the sparse frequency signals to be detected received by each node meet the mixed support set model, and the result of compressive sampling of the radio frequency signals carried by each wavelength is recovered by a joint reconstruction calculation module. Photon distributed compressive sampling may achieve a higher sample rate compression ratio than single-node photon compressive sampling alone to recover a signal.
The radio frequency signal to be tested in the invention is returned to the central station in the mode of optical carrier radio frequency, so that the system has the advantages of long distance and large-range coverage.
The invention has the advantage of large bandwidth of the photonic compressed sampling technology.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive faculty for a person skilled in the art.
Fig. 1 is a schematic structural diagram of a photon-assisted distributed compressive sampling system provided by the present invention.
Fig. 2 is a diagram of two signal primary spectra satisfying the condition of the mixed support set and a diagram of a signal spectrum recovered by single-node photon-assisted compressed sampling.
FIG. 3 is a graph of two signal primary spectra satisfying the condition of the mixed support set and a graph of signal spectra recovered by a photon-assisted distributed compressive sampling system provided by the invention.
Reference numerals in the drawings: 1. the device comprises a multi-wavelength light source, a far-end node, a first wavelength division multiplexer, a first electro-optical modulator, a second wavelength division multiplexer, an antenna, an erbium-doped fiber amplifier (EDFA), a central site, a wavelength division demultiplexer, a second electro-optical modulator, a pseudo-random sequence generator, a photoelectric detector, a low-pass filter, a sampler and a joint reconstruction calculation module, wherein the wavelength division multiplexer comprises the multi-wavelength light source, the far-end node, the first wavelength division multiplexer, the first electro-optical modulator, the second wavelength division multiplexer, the antenna, the erbium-doped fiber amplifier, the EDFA, the central site, the wavelength division demultiplexer, the pseudo-random sequence generator, the photoelectric detector, the low-pass filter, the sampler and the joint reconstruction calculation module.
Detailed Description
It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other.
In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first", "a second", etc. may explicitly or implicitly include one or more such feature. In the description of the present invention, unless otherwise indicated, the meaning of "a plurality" is two or more.
In the description of the present invention, it should be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art in a specific case.
As shown in fig. 1, the invention provides a photon-assisted distributed compressed sampling system, which comprises a first wavelength division multiplexer 3, a first electro-optical modulator 4, a second wavelength division multiplexer 5, an antenna 6, an erbium-doped fiber amplifier EDFA7, a multi-wavelength light source 1 in a central site 8, a wavelength division demultiplexer 9, a second electro-optical modulator 10, a pseudo-random sequence generator 11, a photoelectric detector 12, a low-pass filter 13, a sampler 14 and a joint reconstruction calculation module 15 in a remote node 2 as shown in fig. 1.
The embodiment also provides an implementation method of the photon-assisted distributed compressive sampling system, which comprises the following steps:
the multi-wavelength light source 1 provides continuous light of J wavelengths, lambda 1 ，λ 2 The right of the left of the right of the left of the up to lambda J The multi-wavelength optical carrier is transmitted in a clockwise direction through a single-mode optical fiber to a first remote node 2 where it has a wavelength lambda 1 Is extracted by the first wavelength division multiplexer 3 and the other optical carriers pass directly. The sparse signal of the frequency to be measured received by the antenna 6 is modulated to an optical carrier lambda by the first electro-optic modulator 4 1 The modulated optical signal is then combined with other wavelengths of light by the second wavelength division multiplexer 5 and then transmitted over the optical fiber. In the optical fiber transmission line, an erbium-doped fiber amplifier 7 is added to compensate for the loss of line optical power. Similarly, at the J-th (J represents the wavelength number, J is less than or equal to J) remote node 2, the sparse signal of the frequency to be measured is modulated to the optical carrier lambda by the first electro-optic modulator 4 j Up to the J-th remote node 2.
In this embodiment, each remote node is distributed at a different location by optical fiber connection, and the distances from the signals received by each remote node to the central station are different through optical fibers, so the signals received by each node satisfy the hybrid support set model. The spectrally sparse signals that satisfy the hybrid support set can be modeled as:
wherein the method comprises the steps ofRepresenting the common part of the signal,/>Representing innovative parts of the signal,/->And->Sparse expression can be performed on a certain sparse basis, namely:
wherein W is the fourier orthogonal basis;and->Sparse spectral vectors representing the common part and the innovative part. Common part of each signal in the hybrid support set +.>Not exactly the same, only the frequency points are the same, the amplitudes are different, for each signal the innovative part +.>Is completely independent. Assuming a common partial sparsity of each signal of K c The sparsity of each signal innovation part is K j . Thus, the sparsity of each signal is k=k c +K j For a signal set (x 1 ,x 2 ,...,x j ) WhileIn other words, the sparsity of the signal lumped is +.>
The J sparse signals to be measured received by the J remote nodes 2 are sparse signals in the frequency domain and satisfy the hybrid support set model, so as to represent the correlation between the signals and the signals themselves.
The multi-wavelength optical carrier carrying the J-channel radio frequency information is transmitted back to the central station 8 by the optical fiber. First, the optical carrier wave is decomposed into J paths of optical carrier waves through a wavelength division demultiplexer 9, and each path of optical carrier wave carrying radio frequency information enters a second electro-optical modulator 10 to be mixed with J different pseudo-random sequences generated by a pseudo-random sequence generator 11.
The pseudo-random sequence generator 11 sends out a pseudo-random sequence, and the repetition rate of the pseudo-random sequence must be greater than or equal to the nyquist frequency of the J-path sparse signal, so that the signal after the sparse signal and the pseudo-random sequence are mixed can keep all information of the original sparse signal.
Further, each mixed signal is converted into an electrical signal by a photodetector 12, and then a low-pass filter 13 and a sampler 14 are used to obtain a J-group compressed sampling measurement value sequence y j [n]. Will y j [n]And the signals are sent to a signal joint reconstruction calculation module 15, and the frequency sparse signals to be detected of the J remote nodes 2 are recovered jointly through a distributed compressive sampling reconstruction algorithm.
Specifically, in this embodiment, the j-th remote node receives the sparse signal x of the frequency to be measured j Obtaining an observation value y through photon distributed compressive sampling j 。
The method comprises the following steps:
let the received sparse signal of the jth remote node be x j (t) passing the sparse signal x through a first electro-optic modulator j (t) modulation at wavelength lambda j On the optical carrier wave of (2), the sparse signal x is achieved through a second electro-optic modulator j (t) and pseudo-random binary sequence r j Mixing of (t), and outputting photo-generated current i after passing through the photoelectric detector j (t)∝[1+αx j (t)]·r j (t)＝x′ j (t)·r j (t), wherein alpha is a modulation factor, and after low-pass filtering and downsampling, the compressed sampling system can be represented by the matrix equation: y is j ＝Φ j x j ＝D j H j R j x j Wherein is y j Measurement result, phi j ＝D j H j R j Is a measurement matrix, R j Representing a pseudo-random binary sequence r j (t)，H j Is an impulse response representing a low pass filter, D j Representing the downsampling process of the sampler ADC. Phi j Is a random matrix following a suitable probability distribution, and the matrix product Φ j W satisfies the constraint equidistant condition.
And (3) independently measuring a joint sparse signal X consisting of the frequency sparse signals to be measured received by J nodes through phi to obtain J paths of measured values Y, wherein the measurement process can be expressed as follows:
wherein the method comprises the steps ofIs a set of frequency domain sparse signals satisfying the hybrid support set,represents J-way measurement result, ">Is formed by each signal x j Is of the measurement matrix phi j Diagonal matrix of components>Is a diagonal matrix consisting of J fourier orthogonal basis matrices W,sparse spectrum information representing J signals.
The main objective of this embodiment is to reconstruct the signal set X from the measured value Y simultaneously by joint sparsity in the frequency domain. θ * By solving for the minimum l 1 The problem is completely reconstructed.
And the joint reconstruction calculation module recovers the joint sparse signal X, and the joint reconstruction algorithm is a distributed compressive sampling sparse self-adaptive matching pursuit (DCS-SAMP) algorithm. Compared with the electric domain distributed compressed sampling and single-node photon compressed sampling, the scheme can realize the detection of a larger range of frequency spectrum and higher reconstruction precision.
It should be noted that, the joint reconstruction algorithm mentioned in this embodiment is the same as the distributed compressed sampling recovery algorithm mentioned in the background art, which is the prior art.
Further verifying the validity of this embodiment, in this embodiment comprising two nodes, two sets of signals are set to a common sparsity K c =3, innovating sparsity K 1 ＝K 2 =1. The signal frequency of the first node is set to 0.4GHz, 1.1GHz, 1.5GHz and 1.8GHz, and the signal frequency of the second node is set to 0.4GHz, 1GHz, 1.5GHz and 1.8GHz. The first node and the first electro-optical modulator biased at the orthogonal bias point are modulated to an optical carrier wave, and then are transmitted into the second electro-optical modulator biased at the orthogonal bias point through a section of optical fiber with the length of 20km, and the second electro-optical modulator is mixed with a pseudo-random binary sequence generated by a pseudo-random sequence generator randomly. Photoelectric conversion is carried out by a photoelectric detector with the 3dB bandwidth of 10GHz, and then a compressive sampling measurement result is obtained through a low-pass filter and a sampler. The second node performs photon distributed compressive sampling in the same manner as the first node except that the fiber between the first electro-optic modulator and the second electro-optic modulator is replaced with 10km. The original spectrum and the single-node separate recovery spectrum of the two sets of signals are given in fig. 2 (a) and fig. 2 (b), while the original spectrum and the joint recovery spectrum are given in fig. 3 (a) and fig. 3 (b). At the position ofUnder the condition that the single node is independently recovered, the recovered frequency point is different from the original signal, and the recovery failure is indicated. Under the condition of joint recovery, the system accurately recovers the frequency points of the original signals. This embodiment illustrates that joint recovery has better performance than single-node recovery alone.
The embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the present invention is not limited to the described embodiments. It will be apparent to those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments, including the components, without departing from the principles and spirit of the invention, yet fall within the scope of the invention.
Claims (6)
1. The utility model provides a photon auxiliary distributed compression sampling system, its characterized in that includes central website (8) and a plurality of far-end node (2) that connect gradually, far-end node (2) include first wavelength division multiplexer (3), first electro-optic modulator (4), second wavelength division multiplexer (5) and erbium-doped fiber amplifier (7), first electro-optic modulator (4) set up between first wavelength division multiplexer (3) and second wavelength division multiplexer (5), first electro-optic modulator (4) connect antenna (6) are used for receiving the sparse signal of frequency, central website (8) include multiwave wavelength light source (1), joint reconfiguration calculation module (15) and de-multiplexer (9), be equipped with the sampling module between joint reconfiguration calculation module (15) and de-multiplexer (9), tail end amplifier (7) in far-end node (2) output end and erbium-doped fiber amplifier (7) in the far-end node (2) are connected with the far-end multiplexer (5) input end of the adjacent wavelength division multiplexer (9).
2. A photon assisted distributed compressed sampling system according to claim 1, wherein the sampling module comprises a number of sampling paths comprising a second electro-optical modulator (10), a photodetector (12), a low pass filter (13) and a sampler (14) connected in sequence.
3. A photon-assisted distributed compressed sampling system according to claim 2, wherein a pseudo-random sequence generator (11) is connected to the second electro-optic modulator (10).
4. The implementation method of the photon-assisted distributed compressive sampling system is characterized by comprising the following steps of:
s1, providing continuous light with J wavelengths by a multi-wavelength light source, wherein the wavelength is lambda 1 ，λ 2 ，···，λ J And transmitting to a remote node, said remote node comprising a first wavelength division multiplexer, a first electro-optic modulator, a second wavelength division multiplexer and an erbium-doped fiber amplifier;
s2, extracting wavelength lambda from first wavelength division multiplexer in far-end node 1 Other optical carriers directly pass through;
s3, the frequency sparse signal to be detected is received by the antenna and modulated to an optical carrier lambda through a first electro-optic modulator 1 Then the modulated light signal and other light wavelengths are output by a second wavelength division multiplexer to be combined and then continuously transmitted on the optical fiber;
s4, outputting a combined signal by the second wavelength division multiplexer, and compensating the loss of the optical power of the line through the erbium-doped optical fiber amplifier;
s5, repeating the steps S1-S4, wherein J represents a wavelength sequence number and is less than or equal to J at a J-th remote node, and modulating a frequency sparse signal to be detected to an optical carrier lambda through a first electro-optic modulator j Up to the J-th far-end node and outputting a multi-wavelength optical carrier wave carrying J paths of frequency sparse signals to be tested;
s6, decomposing the multi-wavelength optical carrier carrying J paths of frequency sparse signals to be detected into J paths of optical carriers through a wavelength division demultiplexer;
s7, each path of optical carrier wave respectively enters a second electro-optical modulator and is mixed with J different pseudo-random sequences generated by a pseudo-random sequence generator to obtain J mixed signals;
s8, the mixed signals of each path are converted into electric signals through a photoelectric detector, and then the electric signals are filtered through a low-pass filter andthe sampler obtains a J group compressed sampling measurement value sequence y j [n]；
S9, y j [n]And sending the signals to a signal joint reconstruction calculation module, and jointly recovering the to-be-detected frequency sparse signals of J remote nodes through a distributed compressive sampling reconstruction algorithm.
5. The implementation method of a photon-assisted distributed compressive sampling system according to claim 4, wherein J frequency sparse signals received by J of said remote nodes (2) are frequency domain sparse signals and satisfy a hybrid support set model to represent correlations between signals and signals themselves.
6. The implementation method of a photon-assisted distributed compressive sampling system according to claim 4, wherein the repetition rate of J pseudo-random sequences sent by the pseudo-random sequence generator (11) is not less than the nyquist frequency of the sparse frequency signal to be measured.
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