阅读说明：本技术 基于载噪比的自适应分层小波包变换多径抑制方法及系统 (Carrier-to-noise ratio based adaptive hierarchical wavelet packet transformation multipath suppression method and system ) 是由 马浩 苏明坤 乔磊 仇兆炀 吴超 滕旭阳 宋慧娜 于 2020-12-29 设计创作，主要内容包括：本发明公开了基于载噪比的自适应分层小波包变换多径抑制方法,包括步骤：S1.提取静态模式下参考日数据中包含单颗卫星的多径误差和随机噪声误差的单差残差；S2.基于载噪比CNR约束的自适应分层小波包变换策略抽取多径误差校正模型；S3.采用国际服务IGS站建立多分辨率CNR经验模型；S4.计算相邻历元之间的CNR差值,将计算得到CNR差值与建立的CNR经验模型进行比较,若相邻历元之间的CNR差值相应的波动超过CNR经验模型中的经验值,则通过卫星重复周期转移策略搜索多径校正模型,并通过搜索的多径校正模型中的模型值抑制多径误差；S5.将CNR差值进行双差组合处理,得到校正后的双差观测值,并对校正后的双差观测值进行处理,得到最终的坐标解。(The invention discloses a carrier-to-noise ratio-based adaptive hierarchical wavelet packet transformation multipath suppression method, which comprises the following steps of: s1, extracting single-difference residual errors of multipath errors and random noise errors of a single satellite in reference day data in a static mode; s2, extracting a multipath error correction model based on a carrier-to-noise ratio (CNR) constrained adaptive layered wavelet packet transformation strategy; s3, establishing a multi-resolution CNR empirical model by adopting an international service IGS station; s4, calculating a CNR difference value between adjacent epochs, comparing the calculated CNR difference value with the established CNR empirical model, searching a multipath correction model through a satellite repeated period transfer strategy if the corresponding fluctuation of the CNR difference value between the adjacent epochs exceeds the empirical value in the CNR empirical model, and inhibiting multipath errors through a model value in the searched multipath correction model; and S5, carrying out double-difference combination processing on the CNR difference value to obtain a corrected double-difference observation value, and processing the corrected double-difference observation value to obtain a final coordinate solution.)

1. The multi-path restraining method of the self-adapting layered wavelet packet transformation based on the carrier-to-noise ratio is characterized by comprising the following steps:

s1, extracting single-difference residual errors of multipath errors and random noise errors of a single satellite in reference day data in a static mode;

s2, extracting a multipath error correction model based on a carrier-to-noise ratio (CNR) constrained adaptive layered wavelet packet transformation strategy;

s3, establishing a multi-resolution CNR empirical model by adopting an international service IGS station;

s4, calculating a CNR difference value between adjacent epochs, comparing the calculated CNR difference value with the established CNR empirical model, searching a multipath correction model through a satellite repeated period transfer strategy if the corresponding fluctuation of the CNR difference value between the adjacent epochs exceeds the empirical value in the CNR empirical model, and inhibiting multipath errors through a model value in the searched multipath correction model; if the fluctuation corresponding to the CNR difference value between the adjacent epochs does not exceed the empirical value in the CNR empirical model, not correcting;

and S5, carrying out double-difference combination processing on the CNR difference value to obtain a corrected double-difference observation value, and processing the corrected double-difference observation value to obtain a final coordinate solution.

2. The method for multipath mitigation of adaptive hierarchical wavelet packet transform based on carrier-to-noise ratio according to claim 1, wherein the extraction manner in the step S2 for extracting the multipath error correction model based on the adaptive hierarchical wavelet packet transform strategy constrained by the carrier-to-noise ratio CNR comprises:

when the CNR is larger than 50dB-Hz, 1 layer is selected as a decomposition layer of wavelet packet transformation;

when CNR is distributed between 45dB-Hz and 50dB-Hz, 2 layers are selected as the decomposition layer of wavelet packet transformation;

when CNR is distributed in 40-45 dB-Hz, 3 layers are selected as decomposition layers of wavelet packet transformation;

when the CNR is lower than 40dB-Hz, 4 layers are selected as the decomposition layer of the wavelet packet transform.

3. The method for multipath mitigation of adaptive hierarchical wavelet packet transformation based on carrier-to-noise ratio according to claim 1, wherein the step S3 is performed by using an IGS station to build a multi-resolution CNR empirical model including receiver type, navigation system, and signal frequency.

4. The method as claimed in claim 3, wherein the step S4 of calculating the CNR difference between adjacent epochs is based on a polynomial fitting function in a CNR empirical model.

5. The method for multipath mitigation based on carrier-to-noise ratio adaptive hierarchical wavelet packet transformation of claim 1, wherein the processing of the corrected double-difference observation value in step S5 is performed by least square estimation or kalman filter estimation.

6. A carrier-to-noise ratio based adaptive hierarchical wavelet packet transformation multipath suppression system is characterized by comprising:

the extraction module is used for extracting a single-difference residual error which contains a multipath error and a random noise error of a single satellite in the reference day data in the static mode;

the extraction module is used for extracting a multipath error correction model based on a carrier-to-noise ratio (CNR) constrained adaptive layered wavelet packet transformation strategy;

the construction module is used for establishing a multi-resolution CNR empirical model by adopting an international service IGS station;

the calculation module is used for calculating the CNR difference between the adjacent epochs, comparing the calculated CNR difference with the established CNR empirical model, searching the multipath correction model through a satellite repeated period transfer strategy if the fluctuation of the CNR difference between the adjacent epochs exceeds the empirical value in the CNR empirical model, and inhibiting multipath errors through the model value in the searched multipath correction model; if the fluctuation corresponding to the CNR difference value between the adjacent epochs does not exceed the empirical value in the CNR empirical model, not correcting;

and the correction module is used for carrying out double-difference combination processing on the CNR difference value to obtain a corrected double-difference observation value, and processing the corrected double-difference observation value to obtain a final coordinate solution.

7. The system according to claim 6, wherein the extraction module extracts the extraction mode in the multipath error correction model based on the adaptive hierarchical wavelet packet transform strategy constrained by the carrier-to-noise ratio (CNR), and comprises:

when the CNR is larger than 50dB-Hz, 1 layer is selected as a decomposition layer of wavelet packet transformation;

when CNR is distributed between 45dB-Hz and 50dB-Hz, 2 layers are selected as the decomposition layer of wavelet packet transformation;

when CNR is distributed in 40-45 dB-Hz, 3 layers are selected as decomposition layers of wavelet packet transformation;

when the CNR is lower than 40dB-Hz, 4 layers are selected as the decomposition layer of the wavelet packet transform.

8. The system according to claim 6, wherein the building block uses IGS to build a multiresolution CNR empirical model including receiver type, navigation system, signal frequency.

9. The system according to claim 8, wherein the calculating of the CNR difference between adjacent epochs in the calculating module is based on a polynomial fitting function in an empirical CNR model.

10. The system according to claim 6, wherein the corrected double-difference observations are processed by least squares estimation or Kalman filter estimation in the rectification module.

Technical Field

The invention relates to the technical field of satellite navigation positioning, in particular to a carrier-to-noise ratio-based adaptive hierarchical wavelet packet transformation multipath suppression method and system.

Background

Carrier phase multipath interference is one of the key factors limiting GNSS positioning accuracy because it cannot be eliminated by differential or empirical models. In general, multipath interference can be mitigated by three processing strategies: 1) an antenna strategy; 2) a receiver policy; 3) and (4) data processing strategies. The antenna strategy can only suppress pseudo-range multipath and is ineffective to carrier phase multipath. Receiver techniques can eliminate medium and long delay carrier-phase multipaths but cannot effectively suppress short delay multipath errors. In addition, both antenna and receiver technologies require hardware costs and are difficult to implement in low cost receivers. For these reasons, research on carrier-phase multipath mitigation has focused primarily on data processing strategies. The method based on the post-data processing strategy can be divided into two parts: multipath model extraction and multipath mitigation. For the multipath model extraction method based on wavelet packet transformation, the number of wavelet packet decomposition layers has great influence on the noise reduction effect. If there are too many decomposition layers and fixed threshold processing is performed on the coefficients of each layer, signal information will be lost, resulting in signal degradation and a slow processing speed. However, too few decomposition layers will result in undesirable signal noise reduction.

After the multipath correction model is extracted from the reference day, a search strategy is required to suppress multipath in the subsequent observation day. In a conventional multipath mitigation strategy, all epochs will undergo multipath mitigation decay over the observation day. The main idea of the traditional multipath suppression method is to estimate accurate initial suppression moment by calculating the offset of the satellite orbit repetition period, and then suppress the multipath errors of all epochs one by one through a multipath correction model. However, this inhibition strategy has two distinct disadvantages: 1) the accuracy of multipath mitigation depends to a large extent on the accuracy of the satellite orbit repeat offset, especially for high frequency sample rate data. 2) Multipath mitigation is performed indiscriminately for all epochs, which not only reduces the efficiency of the mitigation, but also reduces the accuracy of the multipath mitigation because not every epoch is affected by multipath.

Disclosure of Invention

The invention aims to provide a method and a system for restraining multipath of self-adaptive layered wavelet packet transformation based on a carrier-to-noise ratio, aiming at the defects of the prior art.

In order to achieve the purpose, the invention adopts the following technical scheme:

a carrier-to-noise ratio based adaptive hierarchical wavelet packet transformation multipath suppression method comprises the following steps:

s1, extracting single-difference residual errors of multipath errors and random noise errors of a single satellite in reference day data in a static mode;

s2, extracting a multipath error correction model based on a carrier-to-noise ratio (CNR) constrained adaptive layered wavelet packet transformation strategy;

s3, establishing a multi-resolution CNR empirical model by adopting an international service IGS station;

s4, calculating a CNR difference value between adjacent epochs, comparing the calculated CNR difference value with the established CNR empirical model, searching a multipath correction model through a satellite repeated period transfer strategy if the corresponding fluctuation of the CNR difference value between the adjacent epochs exceeds the empirical value in the CNR empirical model, and inhibiting multipath errors through a model value in the searched multipath correction model; if the fluctuation corresponding to the CNR difference value between the adjacent epochs does not exceed the empirical value in the CNR empirical model, not correcting;

and S5, carrying out double-difference combination processing on the CNR difference value to obtain a corrected double-difference observation value, and processing the corrected double-difference observation value to obtain a final coordinate solution.

Further, the extracting method in the step S2 of extracting the multipath error correction model based on the carrier-to-noise ratio CNR-constrained adaptive hierarchical wavelet packet transform strategy includes:

when the CNR is larger than 50dB-Hz, 1 layer is selected as a decomposition layer of wavelet packet transformation;

when CNR is distributed between 45dB-Hz and 50dB-Hz, 2 layers are selected as the decomposition layer of wavelet packet transformation;

when CNR is distributed in 40-45 dB-Hz, 3 layers are selected as decomposition layers of wavelet packet transformation;

when the CNR is lower than 40dB-Hz, 4 layers are selected as the decomposition layer of the wavelet packet transform.

Further, in step S3, the multi-resolution CNR empirical model is built by using the international service IGS station, including receiver type, navigation system, and signal frequency.

Further, the step S4 of calculating the CNR difference between adjacent epochs is calculated based on a polynomial fitting function in the CNR empirical model.

Further, the processing of the corrected double-difference observation value in step S5 is performed by least square estimation or kalman filter estimation.

Correspondingly, a carrier-to-noise ratio-based adaptive hierarchical wavelet packet transform multipath suppression system is also provided, which comprises:

the extraction module is used for extracting a single-difference residual error which contains a multipath error and a random noise error of a single satellite in the reference day data in the static mode;

the extraction module is used for extracting a multipath error correction model based on a carrier-to-noise ratio (CNR) constrained adaptive layered wavelet packet transformation strategy;

the construction module is used for establishing a multi-resolution CNR empirical model by adopting an international service IGS station;

the calculation module is used for calculating the CNR difference between the adjacent epochs, comparing the calculated CNR difference with the established CNR empirical model, searching the multipath correction model through a satellite repeated period transfer strategy if the fluctuation of the CNR difference between the adjacent epochs exceeds the empirical value in the CNR empirical model, and inhibiting multipath errors through the model value in the searched multipath correction model; if the fluctuation corresponding to the CNR difference value between the adjacent epochs does not exceed the empirical value in the CNR empirical model, not correcting;

and the correction module is used for carrying out double-difference combination processing on the CNR difference value to obtain a corrected double-difference observation value, and processing the corrected double-difference observation value to obtain a final coordinate solution.

Further, the extraction mode in the extraction module for extracting the multipath error correction model based on the carrier-to-noise ratio CNR constrained adaptive hierarchical wavelet packet transform strategy comprises:

when the CNR is larger than 50dB-Hz, 1 layer is selected as a decomposition layer of wavelet packet transformation;

when CNR is distributed between 45dB-Hz and 50dB-Hz, 2 layers are selected as the decomposition layer of wavelet packet transformation;

when CNR is distributed in 40-45 dB-Hz, 3 layers are selected as decomposition layers of wavelet packet transformation;

when the CNR is lower than 40dB-Hz, 4 layers are selected as the decomposition layer of the wavelet packet transform.

Further, the building module adopts an international service IGS station to build a multi-resolution CNR empirical model which comprises a receiver type, a navigation system and a signal frequency.

Further, the calculating module calculates the CNR difference between adjacent epochs based on a polynomial fitting function in the CNR empirical model.

Further, the processing of the corrected double-difference observation value in the correction module is performed by least square estimation or kalman filtering estimation.

Compared with the prior art, the invention uses the self-adaptive layered wavelet packet transformation denoising model based on the signal CNR constraint, can effectively overcome the defects of signal degradation and slow processing caused by too few or too many decomposition layers and unsatisfactory signal denoising effect, improves the denoising precision and the algorithm stability of the wavelet packet denoising model, and can accurately extract the multipath error correction model, thereby providing powerful guarantee for multipath correction in the subsequent observation day. Meanwhile, the enhanced search strategy under the CNR constraint adopted by the invention can not only improve the multipath inhibition efficiency, but also improve the accuracy of multipath inhibition by executing point-to-point search correction, thereby effectively avoiding the error of multipath inhibition.

Drawings

Fig. 1 is a flowchart of a multipath mitigation method of adaptive hierarchical wavelet packet transform based on carrier-to-noise ratio according to an embodiment;

fig. 2 is a schematic diagram of a carrier-to-noise ratio-based adaptive hierarchical wavelet packet transform multipath mitigation method according to an embodiment;

FIG. 3 is a schematic diagram of the global distribution of IGS stations provided in accordance with one embodiment;

fig. 4 is a diagram of a carrier-to-noise ratio-based adaptive hierarchical wavelet packet transform multipath mitigation system according to the second embodiment.

Detailed Description

The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.

The invention aims to provide a method for adaptively restricting a decomposition layer of wavelet packet transformation to improve the extraction precision of a multipath model and has higher multipath search correction efficiency aiming at the defect of low multipath error correction precision in the prior art.

The invention provides a Carrier Noise ratio constraint-based adaptive layered wavelet packet transformation multipath suppression method and an enhanced search algorithm strategy, which are based on the deep research of the relation between a signal (Carrier Noise ratio) CNR and signal multipath, thereby improving the multipath suppression precision and efficiency of GNSS high-precision positioning.

Example one

The embodiment provides a carrier-to-noise ratio-based adaptive hierarchical wavelet packet transform multipath mitigation method, as shown in fig. 1-2, including the steps of:

s11, extracting single-difference residual errors of multipath errors and random noise errors of a single satellite in reference day data in a static mode;

s12, extracting a multipath error correction model based on a carrier-to-noise ratio (CNR) constrained adaptive layered wavelet packet transformation strategy;

s13, establishing a multi-resolution CNR empirical model by adopting an international service IGS station;

s14, calculating a CNR difference value between adjacent epochs, comparing the calculated CNR difference value with an established CNR empirical model, searching a multipath correction model through a satellite repeated period transfer strategy if the corresponding fluctuation of the CNR difference value between the adjacent epochs exceeds the empirical value in the CNR empirical model, and inhibiting multipath errors through a model value in the searched multipath correction model; if the fluctuation corresponding to the CNR difference value between the adjacent epochs does not exceed the empirical value in the CNR empirical model, not correcting;

and S15, carrying out double-difference combination processing on the CNR difference value to obtain a corrected double-difference observation value, and processing the corrected double-difference observation value to obtain a final coordinate solution.

In step S11, a single difference residual including multipath errors and random noise errors of a single satellite in the reference day data in the static mode is extracted.

And extracting a single difference residual error between receivers only containing a single satellite multipath error and a random noise error from the reference day data in the static mode.

In step S12, a multipath error correction model is extracted based on the carrier-to-noise ratio CNR constrained adaptive hierarchical wavelet packet transform strategy.

The adaptive hierarchical wavelet packet transformation strategy extraction multipath error correction model based on CNR constraint proposed in this embodiment includes the following:

when the CNR is larger than 50dB-Hz, 1 layer is selected as the decomposition layer of the wavelet packet transformation. The main considerations for this option are: the signal CNR is high, in which case the signal quality is good and less affected by noise. Therefore, the number of layers of wavelet packet transform denoising decomposition can be simplified to improve the efficiency of the algorithm.

When the CNR is distributed between 45 and 50dB-Hz, the decomposition layer of the wavelet packet transform selects 2 layers. Although this portion of the signal is less affected by noise and multipath, further processing is still required. Therefore, two layers of wavelet packet transformation are selected for denoising, and both processing efficiency and denoising performance are considered.

When the CNR is distributed at 40 to 45dB-Hz, the decomposition layer of the wavelet packet transformation selects 3 layers. According to experimental data, the CNR distribution of most signals is within this range. Therefore, the part adopts three-layer wavelet packet transformation to denoise signals so as to ensure the overall accuracy of the algorithm.

When the CNR is lower than 40dB-Hz, 4 layers are selected as the decomposition layer of the wavelet packet transform. It can be seen from experimental data that signals with CNR below 40dB-Hz are more severely affected by multipath and noise. Therefore, four-layer wavelet packet transformation is adopted to improve the denoising precision of the partial data.

In step S13, a multi-resolution CNR empirical model is built using the international service IGS station.

And establishing a CNR empirical model, and establishing a multi-resolution CNR model by using an IGS station, wherein the multi-resolution CNR model comprises factors such as a receiver type, a navigation system, signal frequency and the like. The CNR empirical model may also be used as an initial screening test to detect multipath errors.

The global profile of the IGS station is shown in fig. 3.

In step S14, calculating a CNR difference between adjacent epochs, comparing the calculated CNR difference with the established CNR empirical model, if the fluctuation corresponding to the CNR difference between adjacent epochs exceeds the empirical value in the CNR empirical model, searching a multipath correction model through a satellite repetition period transfer strategy, and suppressing a multipath error through a model value in the searched multipath correction model; if the fluctuation corresponding to the CNR difference value between the adjacent epochs does not exceed the empirical value in the CNR empirical model, no correction is carried out.

Calculating the CNR difference between adjacent epochs, comparing the calculated value with an empirical model, searching a multipath correction model through a satellite repeated period transfer strategy if the fluctuation of the difference value of the adjacent epochs exceeds the empirical value, and then performing multipath correction on the epoch through the searched model value; if the set threshold is not exceeded, no correction is made.

Wherein the calculated CNR difference is calculated in an empirical CNR model by a polynomial fitting function.

In step S15, the CNR difference values are subjected to double-difference combination processing to obtain corrected double-difference observed values, and the corrected double-difference observed values are processed to obtain a final coordinate solution.

Carrying out double-difference combination on the obtained single-difference observed values to obtain corrected double-difference observed values; and obtaining a final coordinate solution through least square estimation or Kalman filtering estimation.

The embodiment mainly provides a multi-path restraining method for self-adaptive layered wavelet packet transformation and enhanced search strategy based on CNR constraint. Because the carrier-to-noise ratio (CNR) of the signal is directly related to the multipath error of the signal, the signal can be classified and processed based on the self-adaptive layered wavelet packet transformation under the constraint of the CNR, the error caused by fixing a decomposition layer in the traditional wavelet packet transformation is effectively solved, and the method is different from the traditional wavelet packet transformation denoising. A fixed decomposition layer processing method is adopted in the traditional wavelet packet transformation denoising, and if too many decomposition layers exist, a useful signal is excessively lost, so that the signal denoising effect is degraded and the processing is slow. If the number of the decomposition layers is too small, the noise reduction effect of the polluted signal is not ideal. In the method, the decomposition layer number of wavelet packet transformation is adaptively modulated through CNR constraint, so that the denoising precision and the algorithm stability of a wavelet packet denoising model can be effectively improved, the accuracy of a multipath correction model extracted from a reference day is improved, and powerful guarantee is provided for multipath error attenuation of a subsequent observation day. In addition, the search algorithm in subsequent multipath corrections may also be enhanced by the CNR constraints. The enhanced search strategy has the main advantages that the enhanced search strategy not only can improve the multipath inhibition efficiency, but also can improve the accuracy of multipath error correction by executing point-to-point search correction, thereby effectively avoiding the error generated by integrally correcting all epochs in the traditional multipath correction. In a word, based on the new algorithm provided by the embodiment, not only the extraction accuracy of the multipath correction model on the reference day can be effectively provided, but also the multipath error correction accuracy and efficiency on the subsequent observation day can be effectively provided. In addition, the method of the present embodiment may also be applied to other GNSS static relative positioning applications, such as BDS and Galileo.

Example two

The present embodiment provides a carrier-to-noise ratio based adaptive hierarchical wavelet packet transform multipath mitigation system, as shown in fig. 4, including:

the extraction module 11 is configured to extract a single-difference residual error, which includes a multipath error of a single satellite and a random noise error, from reference daily data in a static mode;

an extraction module 12, configured to extract a multipath error correction model based on a carrier-to-noise ratio CNR-constrained adaptive hierarchical wavelet packet transformation strategy;

the building module 13 is used for building a multi-resolution CNR empirical model by adopting an international service IGS station;

the calculation module 14 is configured to calculate a CNR difference between adjacent epochs, compare the calculated CNR difference with the established CNR empirical model, search the multipath correction model through a satellite repetition period transfer strategy if the fluctuation of the CNR difference between adjacent epochs exceeds an empirical value in the CNR empirical model, and suppress a multipath error through a model value in the searched multipath correction model; if the fluctuation corresponding to the CNR difference value between the adjacent epochs does not exceed the empirical value in the CNR empirical model, not correcting;

and the correction module 15 is configured to perform double-difference combination processing on the CNR difference value to obtain a corrected double-difference observation value, and process the corrected double-difference observation value to obtain a final coordinate solution.

Further, the extraction mode in the extraction module for extracting the multipath error correction model based on the carrier-to-noise ratio CNR constrained adaptive hierarchical wavelet packet transform strategy comprises:

when the CNR is larger than 50dB-Hz, 1 layer is selected as a decomposition layer of wavelet packet transformation;

when CNR is distributed between 45dB-Hz and 50dB-Hz, 2 layers are selected as the decomposition layer of wavelet packet transformation;

when CNR is distributed in 40-45 dB-Hz, 3 layers are selected as decomposition layers of wavelet packet transformation;

when the CNR is lower than 40dB-Hz, 4 layers are selected as the decomposition layer of the wavelet packet transform.

Further, the building module adopts an international service IGS station to build a multi-resolution CNR empirical model which comprises a receiver type, a navigation system and a signal frequency.

Further, the calculating module calculates the CNR difference between adjacent epochs based on a polynomial fitting function in the CNR empirical model.

Further, the processing of the corrected double-difference observation value in the correction module is performed by least square estimation or kalman filtering estimation.

It should be noted that the adaptive hierarchical wavelet packet transform multipath mitigation system based on carrier-to-noise ratio provided in this embodiment is similar to the embodiment, and will not be described herein again.

Compared with the prior art, the embodiment uses the self-adaptive layered wavelet packet transformation denoising model based on the signal CNR constraint, can effectively overcome the defects of signal degradation and slow processing caused by too few or too many decomposition layers and unsatisfactory signal denoising effect, improves the denoising precision and the algorithm stability of the wavelet packet denoising model, and can accurately extract the multipath error correction model, thereby providing a powerful guarantee for multipath correction in the subsequent observation days. Meanwhile, the enhanced search strategy under the CNR constraint adopted by the embodiment can not only improve the efficiency of multipath mitigation, but also improve the accuracy of multipath mitigation by performing point-to-point search correction, thereby effectively avoiding the error of multipath mitigation.

It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.