CN107656254B - Non-orthogonal passive MIMO radar fuzzy function analysis method - Google Patents
Non-orthogonal passive MIMO radar fuzzy function analysis method Download PDFInfo
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Abstract
The invention relates to the field of radar and communication, and aims to analyze whether non-orthogonal waveforms can be used in a passive MIMO radar system or not and further explore a passive radar performance improvement method aiming at the characteristics of a mobile communication illumination source. The technical scheme adopted by the invention is that a non-orthogonal passive MIMO radar fuzzy function analysis method comprises the following steps: the method comprises the following steps: generation of an SCMA signal s (t) based on a user codebook design; step two: a complex envelope form of the transmit waveform; step three: the received signal is represented as:
step four: after a received signal is obtained, a matched filter at a receiving end needs to be discussed; step five: and solving an MIMO passive radar fuzzy function based on the SCMA waveform, and simulating the result by using MATLAB software. The method is mainly applied to the design and manufacture occasions of the non-orthogonal passive MIMO radar.
Description
Technical Field
The invention relates to the field of radar and communication, in particular to non-orthogonal passive MIMO radar fuzzy function analysis.
Background
In recent years, the advantages of passive radar in resisting four threats are receiving wide attention of radar researchers in various countries, and the basic theory of passive radar also makes breakthrough progress. Because the passive radar system only has a receiver, the passive radar system does not emit electromagnetic signals, but utilizes external radiation source signals to detect targets, and therefore the passive radar system has the advantages of being very strong in concealment, high in four-reactance capacity, free of electromagnetic pollution, free of detection blind areas, portable, low in cost and the like.
A Multiple Input Multiple Output (MIMO) radar obtains space diversity gain by using Multiple antennas at the transmitting end and the receiving end of the system[1]Thereby improving the transmission performance of the system on a fading channel. Because the MIMO radar has the advantage of waveform diversity, compared with a phased array radar, the MIMO radar can obtain higher angular resolution, better parameter discrimination capability and interception resistance capability. Therefore, the MIMO radar theory is applied to the passive radar technology, and the characteristics of the transmitter and the receiver can be combined through the joint optimization design of the transmitter and the receiver, so that the performance of the radar for inhibiting various interferences and detecting and identifying targets in a complex environment is improved.
In the early stage of radar research, researchers usually only care about parameters such as time delay and target speed, and along with the complication of a radar system, the correctness and the resolution performance of radar detection must be ensured, so that the researchers propose to analyze the performance of the radar system by using a fuzzy function. The fuzzy function can analyze the characteristics of radar waveform such as resolution, fuzzy and the like, and is an important theoretical basis for analyzing passive radar irradiation source waveforms. Document [2] develops the fuzzy function analysis of bistatic radar, and document [3] generalizes the fuzzy function to MIMO radar, and finds that the larger the number of antennas, the higher the resolution.
With the advent of high-performance AD converters and the increase of available external radiation source signals, passive radars with non-cooperative external radiation sources are gaining increasing attention. Passive radar systems based on various sources of illumination of civil opportunity, such as satellite television signals, fm broadcast signals, GPS signals, etc., have been proposed and studied in succession. In recent years, communication technology has been rapidly developed, and various new technologies have been developed, so that the coverage of communication signals can be continuously expanded, and therefore, various passive radar systems using wireless mobile communication signals as external radiation source signals have gradually become the focus of attention of researchers. Document [4]]The fuzzy function property of the passive radar for moving WIMAX is researched, and the feasibility of the WIMAX signal in the application of the passive radar is proved. Currently, the research of 5 th generation (5G) mobile communication technology is more and more vigorousThroughput, lower latency, better quality of service, and massive links will be the design pursuits of 5G systems. Thus, sparse code division multiple access (SCMA) techniques[5]Due to the characteristics of excellent throughput performance and wrapped access, the method becomes the research focus of the 5G multiple access at present. Therefore, in the research of the passive MIMO radar field, the non-orthogonal waveform is researched to serve as a radar radiation source signal, the development trend of the communication technology is complied with, and a new thought and scheme can be provided for the research of the radar technology.
[1] Chenhao wen, li xiang, zhuangzhao wen a new radar system-MIMO radar [ J ] electronics report, 2012, 40 (6): 1190-1198.
[2]Tsao T,Slamani M,Varshney P,et al.Ambiguity function for a bistatic radar[J].IEEE Trans Aerosp Electron Syst,1997,33(3):1041-1051.
[3]G A Antonio,D R.Fuhrmann,and F C.Robey.MIMO Radar Ambiguity Functions[J].IEEE Journal of Selected Topics in Signal Processing,2007,1(1):167-177.
[4] Wanqing, Houckweed, Lu Yi-Long, Passive Radar Signal analysis and fuzzy function Property Studies based on Mobile WiMAX [ J ] computer application Studies, 2010, (06):2226-2228.
[5]M.Taherzadeh,H.Nikopour,A.Bayesteh and H.Baligh.SCMA Codebook Design[C].2014 IEEE 80th Vehicular Technology Conference(VTC2014-Fall),Vancouver,BC,2014,pp.1-5。
Disclosure of Invention
In order to overcome the defects of the prior art, the invention aims to analyze whether the non-orthogonal waveforms can be used in a passive MIMO radar system or not, and further explore a passive radar performance improvement method aiming at the characteristics of a mobile communication illumination source. The technical scheme adopted by the invention is that a non-orthogonal passive MIMO radar fuzzy function analysis method comprises the following steps:
the method comprises the following steps: generation of SCMA signal s (t) based on user codebook design: firstly, designing a mother constellation diagram, then carrying out constellation diagram operation on the mother constellation diagram to finally obtain a suboptimal user codebook, and finally generating a sparse code division multiple access SCMA signal S (t) according to the user codebook;
step two: the transmitting antennas are isotropic and there is no coupling between the antennas, each antenna being capable of transmitting an independent SCMA signal waveform, all of which have the same bandwidth B and duration T and are modulated to the same center frequency fcAbove, the signal bandwidth satisfies the condition B/2>fcThen the complex envelope form of the transmit waveform is represented as:
wherein s isi(t) is the complex envelope of the ith signal waveform;
step three: the signal received by the jth receive antenna before it has not been demodulated to baseband is represented as:
wherein the content of the first and second substances,
denoted is the background noise for the jth receive antenna, generally modeled as a known energy of n0White noise, amplitude coefficient of
Is a complex representation of the scattering functions of the (i, j) transmit-receive channels, all of which are considered to be identical in a coherent scattering model, i.e.
After demodulation, the received signal is represented as:
step four: after obtaining the received signal, the matched filter at the receiving end needs to be discussed, and the subscript used below
Representing the filter ordinal number, corresponding to the ordinal number of the waveform of the signal to which the filter is matched, at the jth receive antenna, and at the jth receive antenna
The output of the transmit waveform matched filtering is:
in the formula, theta1,θ2Incident parameters for signal 1 and signal 2 respectively,
the abstract expression is obtained after noise is output through matched filtering.
Step five: according to definition of fuzzy function
And solving an MIMO passive radar fuzzy function based on the SCMA waveform, and simulating the result by using MATLAB software.
The invention has the characteristics and beneficial effects that:
the MIMO radar fuzzy function is analyzed and deduced based on the analysis of the SCMA technical codebook design problem, the non-orthogonal signal in the SCMA system is used as a radiation source signal of the radar, the radar waveform performance of the non-orthogonal waveform is simulated and analyzed, the feasibility of the non-orthogonal radar waveform is verified, the Doppler performance of the system can be improved when the method is applied to the MIMO radar, and new guidance can be provided for the MIMO radar waveform optimization.
Description of the drawings:
fig. 1 is a three-dimensional diagram of a MIMO ambiguity function based on SCMA signals.
Fig. 2 is a distance profile of a MIMO ambiguity function based on SCMA signals.
Figure 3 is a doppler profile of a MIMO ambiguity function based on SCMA signals.
Fig. 4 signal processing flow.
Detailed Description
The invention belongs to the field of radar and communication, applies non-orthogonal signals of a 5G communication system to passive radar research, and introduces an MIMO radar theory to improve the overall performance of a radar system. Simulation results prove that the non-orthogonal waveforms can be used for passive MIMO radar and provide guidance for passive MIMO radar waveform research.
In the future radar system design, passive radar, waveform diversity, bionic design and cognitive methods are effective methods for solving spectrum congestion from the viewpoint of improving the utilization rate of spectrum resources. The invention takes SCMA non-orthogonal signals with high frequency spectrum utilization rate as radar radiation source signals, aims to analyze whether non-orthogonal waveforms can be used in a passive MIMO radar system, and further explores a passive radar performance improvement method aiming at the characteristics of a mobile communication radiation source. Meanwhile, the 5G non-orthogonal waveform is used as a passive radar illumination source, which is a new problem in compliance with the development trend of the technology.
Although some progress has been made in the research of the non-orthogonal multiple access technology of the 5G system, the research still needs the common effort of researchers in the aspect of practical application, and the main research still stays in the experimental simulation stage at present, so the passive MIMO radar fuzzy function is mainly derived for the SCMA signal, the MATLAB software is used for carrying out simulation analysis on the performance of the passive MIMO radar, the specific simulation result is used for verifying the theory, and the performance of the key technology is improved. The MATLAB process flow is shown in fig. 4 below:
the detailed steps are as follows:
the method comprises the following steps: generation of SCMA signal s (t) based on user codebook design. The user codebook design is the key of the SCMA technology, firstly, a mother constellation diagram is designed, then, the mother constellation diagram is subjected to constellation diagram operation, and finally, a suboptimal user codebook is obtained. Finally, an SCMA signal s (t) is generated from the user codebook.
Step two: assuming isotropic transmit antennas and no coupling between the antennas, each antenna is capable of transmitting an independent SCMA signal waveform, all of which have the same bandwidth B and durationOf duration T and all modulated to the same centre frequency fcIn the above, it is assumed that the signal bandwidth satisfies the condition B/2>fcThen the complex envelope form of the transmit waveform can be expressed as:
wherein the content of the first and second substances,
si(t) is the complex envelope of the ith signal waveform.
Step three: the signal received by the jth receive antenna before it has been demodulated to the baseband signal may be expressed as:
wherein the content of the first and second substances,
denoted is the background noise for the jth receive antenna, generally modeled as a known energy of n0White noise of (2). Coefficient of amplitude
Is a complex representation of the scattering functions of the (i, j) transmit-receive channels, all of which can be considered identical under a coherent scattering model, i.e.
After demodulation, the received signal can be expressed as:
step four: after obtaining the received signal, the matched filter at the receiving end needs to be discussed, and the subscript used below
Represented is the filter ordinal number, corresponding to the ordinal number of the signal waveform to which the filter is matched. At the jth receiving antenna, with
The output of the transmit waveform matched filtering is:
in the formula, theta1,θ2Incident parameters for signal 1 and signal 2 respectively,
the abstract expression is obtained after noise is output through matched filtering.
Step five: according to definition of fuzzy function
And (3) solving an MIMO passive radar fuzzy function based on an SCMA waveform, and simulating the result by using MATLAB software, wherein the results are shown in figures 1 to 3.
Claims (1)
1. A non-orthogonal passive MIMO radar fuzzy function analysis method is characterized by comprising the following steps:
the method comprises the following steps: generation of SCMA signal s (t) based on user codebook design: firstly, designing a mother constellation diagram, then carrying out constellation diagram operation on the mother constellation diagram to finally obtain a suboptimal user codebook, and finally generating a sparse code division multiple access SCMA signal S (t) according to the user codebook;
step two: the transmitting antennas are isotropic and there is no coupling between the antennas, each antenna being capable of transmitting an independent SCMA signal waveform, all of which have the same bandwidth B and duration T and are modulated to the same center frequency fcAbove, the signal bandwidth satisfies the condition B/2>fcThen the complex envelope form of the transmit waveform is represented as:
wherein s isi(t) is the complex envelope of the ith signal waveform;
step three: the signal received by the jth receive antenna before it has not been demodulated to baseband is represented as:
wherein the content of the first and second substances,
denoted is the background noise for the jth receive antenna, generally modeled as a known energy of n0White noise, amplitude coefficient of
Is a complex representation of the scattering functions of the (i, j) transmit-receive channels, all of which are considered to be identical in a coherent scattering model, i.e.
After demodulation, the received signal is represented as:
step four: after obtaining the received signal, the matched filter at the receiving end needs to be discussed, and the subscript used below
Representing the filter ordinal number, corresponding to the ordinal number of the waveform of the signal to which the filter is matched, at the jth receive antenna, and at the jth receive antenna
The output of the transmit waveform matched filtering is:
in the formula, theta1,θ2Incident parameters for signal 1 and signal 2 respectively,
the noise is an abstract expression after being output by matched filtering;
step five: according to definition of fuzzy function
And solving an MIMO passive radar fuzzy function based on the SCMA waveform, and simulating the result by using MATLAB software.
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