CN105301557A - Direction-of-arrival estimate configuration method - Google Patents
Direction-of-arrival estimate configuration method Download PDFInfo
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- CN105301557A CN105301557A CN201510750947.9A CN201510750947A CN105301557A CN 105301557 A CN105301557 A CN 105301557A CN 201510750947 A CN201510750947 A CN 201510750947A CN 105301557 A CN105301557 A CN 105301557A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S3/00—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
- G01S3/02—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using radio waves
- G01S3/14—Systems for determining direction or deviation from predetermined direction
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Abstract
The invention provides a direction-of-arrival estimate configuration method, and particularly provides a direction-of-arrival estimate configuration method facing the broadband wireless communication intelligent antenna system. The direction-of-arrival estimate configuration method comprises steps of adopting a MUSIC/ESPRIT algorithm to obtain a DOA estimate result when a real signal to noise ratio is greater than or equal to a signal to noise ratio threshold, adopting an ML/WSF algorithm evaluation criterion to process the signal data received by the antenna array when the real signal to noise ratio is smaller than the a signal to noise ratio threshold, performing analyzing processing on the ML/WSF algorithm evaluation to obtain a DOA estimate final value, using the DOA estimate result as an original value which is obtained through the MUSIC/ESPRIT in the process of analyzing and processing the ML/WSF algorithm, and obtaining a search value in proximity to the original value as the DOA estimate final value through the local searching.
Description
Technical field
The present invention relates to a kind of ripple and reach orientation estimation framework method, particularly a kind of ripple towards broadband wireless communications antenna system reaches orientation estimation framework method.
Background technology
Smart antenna (smartantenna) technology is one of gordian technique of the 3G international standard TD-SCDMA that China independently proposes, capacity and the antijamming capability of wireless communication system can be significantly improved, be widely used in current TD-LTE (4G) system, and will be one of the gordian technique of following 5G communication system.In the General System of smart antenna is as shown in Figure 1 formed, core comprises three parts: aerial array (AntennaArray), ripple reach orientation and estimate (DOA) module and beam forming (AdaptiveAlgorithm) module.
The aerial array of antenna system generally adopts adaptive antenna array, the core methed of adaptive antenna array is the difference utilizing the orthogonality in multiple antenna element space and each subscriber signal space characteristics, take data antenna technology, automatically the weighing vector (W*) of antenna array is regulated according to certain acceptance criteria, produce dimensional orientation wave beam, make antenna main beam aim at the arrival direction of subscriber signal, secondary lobe or zero trapping spot aim at undesired signal arrival direction.Thus improve the Signal to Interference plus Noise Ratio (SignaltoInterferenceandNoiseRatio, SINR) of targeted customer.The principle of work of adaptive antenna array as shown in Figure 2.
As depicted in figs. 1 and 2, a key modules of antenna system is: ripple reaches orientation and estimates (Directional-of-Arrival, DOA) module.
Antenna system in the past needs the ripple of estimating target signal and interference source exactly to reach orientation (DOA), and with the arrival direction making antenna main beam aim at subscriber signal, secondary lobe or zero trapping spot aim at undesired signal arrival direction.Large quantity research and system testing show that DOA estimates to affect to a great extent the performance of smart antenna, and then affect the bit error rate of whole system, power system capacity and coverage.
In current antenna system, what the ripple DOA algorithm for estimating reached in orientation estimation (DOA) module generally adopted is multiple signal classification (MUSIC:MultipleSignalClassification) algorithm and invariable rotary parameter estimation algorithm (ESPRIT:EstimationofSignalParametersviaRotationalInvarian ceTechniques).The main feature of these 2 kinds of algorithms is that DOA estimated accuracy is higher and computation complexity is lower when signal to noise ratio (S/N ratio) (SNR, signaltonoiseratio) is higher.
But MUSIC algorithm and ESPRIT method are when SNR (Signal-to-NoiseRatio) is lower, and resolving accuracy is not high.In addition a significant deficiency is also had to be that these class methods directly can not process multipath signal.When signal has multipath conditions to occur, MUSIC method and ESPRIT method must adopt pre-service to carry out decorrelation LMS, as space smoothing (SpatialSmoothing) process or matrix reconstruction etc.Pre-service adds the complexity of system on the one hand, also can affect the precision of DOA estimation or the array aperture of sacrificial system etc. on the other hand.
Compare MUSIC and ESPRIT algorithm, weight subspace fitting (WSF:WeightedSubspaceFitting) and maximum likelihood (ML, MaximumLikelihood) be more advanced algorithm, it directly can process multipath signal without pre-service.And when signal to noise ratio snr is lower, the DOA estimated accuracy of WSF and ML algorithm is also higher.But the solution procedure of WSF and ML is the optimization procedure of a multidimensional nonlinear multi-peak, therefore its computation complexity will exceed much compared to MUSIC and ESPRIT.This is also the topmost reason stoping WSF and ML algorithm to be applied in systems in practice at present.
Shown in the block diagram of the flow process estimated as DOA in the antenna system of Fig. 3, in traditional process, the SNR size no matter receiving data how, is all the traditional process adopted as shown in Figure 3.But as described above, MUSIC/ESPRIT algorithm is when SNR is lower, and the precision that its DOA estimates is low-down, therefore, plays very important impact to the performance of whole system.But the resolving of ML/WSF algorithm is the optimization problem of a multidimensional nonlinear, and its computation complexity is very high.
When signal to noise ratio snr is lower, the DOA estimated accuracy of MUSIC/ESPRIT algorithm is lower, for overcoming this shortcoming, ripple of the present invention reaches orientation and estimates that framework method proposes a kind of ripple combined based on MUSIC/ESPRIT algorithm and ML/WSF algorithm and reaches orientation estimation framework method.
For effectively reducing the computation complexity of ML/WSF, and the DOA estimated accuracy improved when SNR is lower, present invention further proposes and adopt with the DOA estimated result of MUSIC/ESPRIT algorithm as initial value, then adopt the method for Local Search, a kind of ripple finding the end value that the search value near initial value is estimated as DOA reaches orientation and estimates framework method.
Summary of the invention
For the shortcoming that the computation complexity overcoming above-mentioned ML/WSF is higher, effective raising ripple reaches orientation estimated accuracy, estimated accuracy particularly when low SNR, comprising aerial array (AntennaArray), ripple reaches orientation and estimates in the antenna system of (DOA) module and these three parts of beam forming (AdaptiveAlgorithm) module, and ripple of the present invention reaches orientation and estimates that framework method comprises the following steps:
Preset the step of snr threshold;
From described antenna array receiver signal data, draw the step of actual signal to noise ratio (S/N ratio) from described signal data;
The size of described actual signal to noise ratio (S/N ratio) and described snr threshold is compared, be divided into described actual signal to noise ratio (S/N ratio) to be more than or equal to the situation of described snr threshold, and described actual signal to noise ratio (S/N ratio) is less than the step of the situation of described snr threshold;
When described actual signal to noise ratio (S/N ratio) is more than or equal to described snr threshold, MUSIC/ESPRIT algorithm is adopted to draw the step of DOA estimated result;
When described actual signal to noise ratio (S/N ratio) is less than described snr threshold, adopt evaluation criterion (criterion) process of ML/WSF algorithm from described antenna array receiver to described signal data, next, dissection process is carried out to the described evaluation criterion of ML/WSF algorithm, draws the step of the end value that DOA estimates.
Wherein, carrying out in the process of described dissection process to the described evaluation criterion of ML/WSF algorithm, the described DOA estimated result drawn using MUSIC/ESPRIT algorithm, as initial value, by Local Search, draws the end value that the search value near described initial value is estimated as DOA.
Ripple according to the present invention reaches orientation and estimates framework method, and when SNR is lower, the precision that DOA is estimated is improved.
Accompanying drawing explanation
In order to be illustrated more clearly in the technical scheme in the embodiment of the present invention, below the accompanying drawing used required in describing the embodiment of the present invention is briefly described, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to the content of the embodiment of the present invention and these accompanying drawings.
Fig. 1 is that medelling represents the figure that antenna system is formed.
Fig. 2 is the figure that medelling represents the basic functional principle of adaptive antenna array in smart antenna.
Fig. 3 is that medelling represents the traditional process of DOA estimation and the figure of flow process of the present invention in smart antenna of the present invention.
Embodiment
Traditional DOA estimates that framework is: after antenna array receiver to data, directly apply mechanically the evaluation criterion of MUSIC (multiple signal classification) or ESPRIT (Signal parameter estimation of Subspace Rotation unchangeability) algorithm, data are processed, and then the DOA obtaining signal source estimates.
Based on this, the present invention proposes a kind of ripple that can effectively improve newly and reaches the framework that (particularly in the situation of low SNR) is estimated in orientation, and its flow process as shown in Figure 3.Comprising aerial array (AntennaArray), ripple reaches orientation and estimates in the antenna system of (DOA) module and these three parts of beam forming (AdaptiveAlgorithm) module, and ripple of the present invention reaches orientation and estimates that framework method comprises the following steps: the step presetting snr threshold; From described antenna array receiver signal data, draw the step of actual signal to noise ratio (S/N ratio) from described signal data; The size of described actual signal to noise ratio (S/N ratio) and described snr threshold is compared, be divided into described actual signal to noise ratio (S/N ratio) to be more than or equal to the situation of described snr threshold, and described actual signal to noise ratio (S/N ratio) is less than the step of the situation of described snr threshold; When described actual signal to noise ratio (S/N ratio) is more than or equal to described snr threshold, MUSIC/ESPRIT algorithm is adopted to draw the step of DOA estimated result; When described actual signal to noise ratio (S/N ratio) is less than described snr threshold, adopt evaluation criterion (criterion) process of ML/WSF algorithm from described antenna array receiver to described signal data, next, dissection process is carried out to the described evaluation criterion of ML/WSF algorithm, draws the step of the end value that DOA estimates.Wherein, carrying out in the process of described dissection process to the described evaluation criterion of ML/WSF algorithm, the described DOA estimated result drawn using MUSIC/ESPRIT algorithm, as initial value, by Local Search, draws the end value that the search value near described initial value is estimated as DOA.
SNR threshold value, can define amendment flexibly by system.Herein for 10dB.
Idiographic flow is as follows:
1., as SNR>=10dB, flow process is carried out ripple and is reached orientation estimation directly to adopt traditional DOA to estimate, as shown in Figure 3.
2. as SNR<10dB:
1) traditional DOA first, is still adopted to estimate the DOA result that flow process is estimated to calculate MUSIC/ESPRIT algorithm;
2) evaluation criterion of ML/WSF algorithm is adopted to process the data received;
3) in the process of the parsing of ML/WSF algorithm, using the 1st) result estimated by step is as initial value.Adopt the method for Local Search, find optimal value near initial value as DOA estimated result.
Ripple according to the present invention reaches orientation and estimates framework method, and based on the method for adopted Local Search, when not increasing computation complexity, when SNR is lower, the precision that DOA is estimated is improved.
Above embodiments of the present invention are illustrated, but this embodiment is only as an example, not there is the intention limiting invention scope.The present invention can be implemented by other various forms, can carry out various change in the scope not exceeding inventive concept.
Claims (2)
1. a ripple reaches orientation estimation framework method, it is characterized in that, comprising aerial array (AntennaArray), ripple reaches orientation and estimates in the antenna system of (DOA) module and these three parts of beam forming (AdaptiveAlgorithm) module, and ripple reaches orientation and estimates that framework method comprises the following steps:
Preset the step of snr threshold;
From described antenna array receiver signal data, draw the step of actual signal to noise ratio (S/N ratio) from described signal data;
The size of described actual signal to noise ratio (S/N ratio) and described snr threshold is compared, be divided into described actual signal to noise ratio (S/N ratio) to be more than or equal to the situation of described snr threshold, and described actual signal to noise ratio (S/N ratio) is less than the step of the situation of described snr threshold;
When described actual signal to noise ratio (S/N ratio) is more than or equal to described snr threshold, MUSIC/ESPRIT algorithm is adopted to draw the step of DOA estimated result;
When described actual signal to noise ratio (S/N ratio) is less than described snr threshold, adopt evaluation criterion (criterion) process of ML/WSF algorithm from described antenna array receiver to described signal data, next, dissection process is carried out to the described evaluation criterion of ML/WSF algorithm, draws the step of the end value that DOA estimates.
2. ripple according to claim 1 reaches orientation estimation framework method, it is characterized in that,
Carrying out in the process of described dissection process to the described evaluation criterion of ML/WSF algorithm, the described DOA estimated result drawn using MUSIC/ESPRIT algorithm is as initial value, by Local Search, draw the end value that the search value near described initial value is estimated as described DOA.
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| CN110308418A (en) * | 2019-08-06 | 2019-10-08 | 中国石油大学(华东) | A kind of DOA estimation framework method |
| CN110554352A (en) * | 2019-09-11 | 2019-12-10 | 哈尔滨工业大学 | Method for estimating direction of arrival of interference source of aerospace measurement and control system based on VGG16 neural network |
| CN112180317A (en) * | 2020-09-10 | 2021-01-05 | 中国石油大学(华东) | DOA estimation algorithm of non-uniform over-complete dictionary based on priori knowledge |
| CN112698092A (en) * | 2020-12-11 | 2021-04-23 | 国网辽宁省电力有限公司葫芦岛供电公司 | Rapid broadband measuring device and method based on ESPRIT algorithm |
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Cited By (5)
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| CN112698092A (en) * | 2020-12-11 | 2021-04-23 | 国网辽宁省电力有限公司葫芦岛供电公司 | Rapid broadband measuring device and method based on ESPRIT algorithm |
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Application publication date: 20160203 |