KR101090341B1 - A range estimation algorithm with low complexity based on ieee 802.15.4a chirp spread spectrum - Google Patents

Abstract

PURPOSE: A range estimation algorithm with low complexity based on IEEE.802.15.4a chirp spread spectrum is provided to calculate delay time through an effective pre-process to attenuate interferences such as a multi-path, thereby increasing range estimation performance under an inner environment. CONSTITUTION: A sub chirp is realized by white Gaussian noise and a multi channel. A de-chirped sub chirp is obtained by a pre-process which obtains exact time. A sine signal with delay time information as a frequency component is obtained through the de-chirped sub chirp. The sine signal is divided into a signal and a noise by singular value decomposition. The delay time of each path is obtained by using an algorithm based on a noise space such as an ESPRIT(Estimation of Signal Parameter via Rotation Invariant Technique) and an MP(Matrix Pencil).

Description

A range estimation algorithm with low complexity based on IEEE 802.15.4a chirp spread spectrum}

The present invention relates to an ultra wide band (UWB) wireless communication system and a method thereof, and more particularly, through an effective preprocessing process in a wireless communication system based on the IEEE 802.15.4a chirp spread spectrum. A low complexity ranging algorithm based on an IEEE 802.15.4a chirp spread spectrum for presenting an algorithm for calculating latency.

Conventionally, the IEEE standard 802.15.4 was established to provide a basic lower network layer of a wireless personal communication network (WPAN). In particular, the IEEE standard 802.15.4 is aimed at low-cost, low-speed ubiquitous communication between devices.

In other words, IEEE 802.15.4 enables low-cost communication between devices in close proximity to each other without a special infrastructure, and also has low power consumption in mind. The basic framework of IEEE 802.15.4 is within 10 meters of the distance. Assuming a transfer rate of 250 kbit / s, various types of physical layers are defined, not just one type of physical layer.

In other words, it is defined as multiple physical layers to trade off for embedded systems that require less power consumption.In the original low-speed specification, the transfer rate was about 20 and 40 kbit / s, but the current version is about 100 kbit / s. This was added.

In addition, the lower power consumption specification may also consider lower transfer rates than these. However, as described above, only the features of the IEEE 802.15.4 standard in the WPAN standard pursue extremely low manufacturing cost and technical simplicity. This should be done without compromising technical flexibility and generality.

Important features included in IEEE 802.15.4 include the ability to reserve time slots for real-time applications, collision reporting with CSMA / CA, and secure communication support. Manufacturers can include power management features such as link quality and energy detection in their devices.

IEEE 802.15.4 devices operate in one of three possible radio frequency bands, that is, the PHY operates at 2450 MHz (2400-2483.5), 868 MHz (868-868.6), and 915 MHz (902-928).

In addition, there is a sensor network as one of the technologies actively researched around the world with the expansion of the ubiquitous paradigm for accessing a computing environment anytime, anywhere regardless of a human center.

The sensor network refers to a sensor network. The sensor network is also referred to as a wireless sensor network (WSN), a ubiquitous sensor network (USN), and the like. It has the following features.

First, USN technology is largely embedded contents such as RFID, WSN, embedded wireless network technology applied to all things. Second, USN related software platforms include TinyOS, Nano Qplus, Contiki, LiteOS, Third, USN standards include ZigBee [4], Wireless HART [5], ISA 100 [6] along with IETF's 6LoWPAN [1], ROLL [2] and CoRE [3]. Etc.

In addition, in the next two to three years, the USN technology that combines IPv6 is expected to spread, and legislation and standardization are in progress at home and abroad.

In other words, the ubiquitous sensor network (USN) refers to a network configured to collect information collected by various sensors wirelessly. When hundreds of sensor network nodes are installed in vulnerable areas where humans cannot access, It can play the same role.

With the development of WPAN (Wireless Personal Area Network) technology and micro network device technology, sensor network technology is very active. For example, in the United States, this technology is being applied to home automation and ecological monitoring. These technologies could be widely used in future infrastructure safety monitoring, forest fire monitoring, industrial facility monitoring, and defense.

For this reason, the most important technology in USN is reliability that delivers accurate information quickly, and power consumption is also very important.

Therefore, although low-speed ultra wide band (UWB) technology of IEEE 802.15.4a, which is one of wireless personal area network (WPAN) transmission technologies, has been actively studied, the WPAN transmission channel proposed by IEEE 802.15.4a is seriously studied. There is a multi-path interference component and there is an urgent need for a solution.

In more detail, due to the characteristics of the radio signal, interference with other wireless communication systems (for example, Bluetooth, Wi-Fi, etc.) that actually use the same frequency band, or body factor Communication failures due to other media such as factors) occur.

Here, the body factor refers to a situation in which wireless radio communication is disturbed by a human body. For example, in the case of a system based on IEEE 802.15.4, which is widely used in a conventional sensor network, two sensor nodes are used. If you try to communicate by attaching to the front and back of the body, the communication itself is often impossible, and this phenomenon is similar in CSS-based IEEE 802.15.4a.

In actual experiments, communication is often impossible in the open air, and indoors, radio waves are received through various paths due to multipath by reflected waves such as walls, and packet reception is possible, but due to time of arrival (TOA) Due to the characteristics of the IEEE 802.15.4a method of measuring distance, an error occurs with a distance larger than the actual distance.

Also, with the advent of the ubiquitous era, interest in indoor location tracking systems has increased socially, but existing indoor location tracking systems do not actively respond to frequent changes in the indoor environment, and due to the NLOS characteristics of the indoor environment, Accurate positioning was difficult.

Therefore, it is desirable to solve the problems of the conventional IEEE 802.15.4a based UWB communication system as described above, to solve the problem of multipath interference and to provide a low complexity algorithm capable of processing a plurality of signals at one time. There is no device or method that satisfies all the requirements.

The present invention seeks to solve the problems of the prior art as described above. Accordingly, an object of the present invention is to cancel the interference component such as multipath to improve the distance measuring performance in an indoor environment, By presenting an algorithm that can process a signal at a time, it is to provide a low complexity distance measuring method of an IEEE 802.15.4a based ultra wideband wireless communication system in a distance measuring and positioning system using ultra wideband (UWB) communication. .

In order to achieve the above object, according to the present invention, to calculate the delay time to measure the distance in the ultra-wideband (Ultra Wide Band) wireless communication system based on IEEE 802.15.4a chirp Spread Spectrum In the IEEE 802.15.4a chirp spread-spectrum-based low complexity ranging algorithm used to obtain a subchirp through white Gaussian noise and multichannels, and a preprocessing process to obtain accurate time obtaining a de-chirped sub chirp, and obtaining a sine signal having delay information as a frequency component through the depacked subchirp, and performing signal and noise space through singular value decomposition. ), Followed by noise such as Estimation of Signal Parameter via Rotation Invariant Technique (ESPRIT) and Matrix Pencil (MP). And calculating a delay time of each pass using a subspace based algorithm, wherein the preprocessing is performed by using the first subfolder of the symbol based on the IEEE 802.15.4a chirp spread spectrum piconet 1 and 2 The de-subfolded subfold is obtained through a preprocessing process using de-folded subfolds of subfolders having the same slope and different bands in the time-frequency domain, like the first subfolder, or the third and fourth subfolders. Thereby an IEEE 802.15.4a chirp spread spectrum based low complexity ranging algorithm is provided which is configured to reduce the complexity of the calculation of the overall algorithm for calculating the delay by calculating the delay.

Here, the step of obtaining the sub-pouch, m is the index of the path (d), d is the number of paths, the amplitude of the m-th path a _m , the delay time of the m-th path τ _m , n (t) is white In the case of Gaussian noise, the sub-chirp is obtained using Equation 1 below.

[Equation 1]

In the calculating of the delay time, the delay time may be calculated using Equation 3 below.

[Equation 3]

In addition, in the pretreatment process, p is a sample index, and Ts is a sampling interval.

[Equation 2]

IEEE 802.15.4a chirp Spread Spectrum Piconet 1, 2nd de-subfold the subfolder can be expressed as the following [Equation 4] and [Equation 5],

[Equation 4]

[Equation 5]

From the above [Equation 4] and [Equation 5], since the frequency information is the same and the phase information is different, the frequency information having the original delay time information is included even when the [Equation 4] and [Equation 5] are averaged. Based on the fact that a signal can be obtained, the defolded subfolder is obtained using Equation 6 below.

[Equation 6]

As described above, according to the present invention, in a distance measurement and position measurement system using ultra wide band (UWB) communication, an algorithm for calculating delay time through an effective preprocessing process is provided, thereby canceling an interference component such as a multipath. A low complexity ranging algorithm based on IEEE 802.15.4a chirp spread spectrum is provided to improve the distance measurement performance in an indoor environment and to simultaneously process a plurality of signals.

Therefore, according to the present invention, in the ultra-wideband wireless communication system based on IEEE 802.15.4a, it is possible to provide a distance measurement and location measurement system using ultra-wideband (UWB) communication with improved distance measurement performance in an indoor environment.

1 is a view showing a comparison of the magnitude of the signal before and after applying the algorithm according to the present invention.
2 is a view showing a result of comparing the conventional algorithm and the algorithm according to the present invention, respectively.
3 is a view showing a result of comparing the conventional algorithm and the algorithm according to the present invention, respectively.

Hereinafter, with reference to the accompanying drawings, the details of the low complexity distance measuring method of the ultra-wideband wireless communication system according to the present invention will be described.

Hereinafter, it is to be noted that the following description is only an embodiment for carrying out the present invention, and the present invention is not limited to the contents of the embodiments described below.

As described above, with the advent of the ubiquitous network era, a location-aware wireless personal area network (WPAN) system is attracting attention due to an increasing demand for location-based application services, and in particular, the ultra-wideband (UWB) technology has a low cost. It is recognized as a core technology for building ubiquitous homes because it can provide precise location recognition and tracking function within tens of centimeters in indoor or shaded areas as well as communication with low power consumption.It is recognized as a core technology for establishing low speed location recognition WPAN standard IEEE 802.15 It is adopted as the physical layer (PHY) of .4a.

In other words, UWB radio technology refers to a technology that occupies 20% or more of the center frequency bandwidth or 500MHz or more, and has a relatively low spectral power over a very wide frequency band compared to a conventional narrowband system or a wideband CDMA system. Because of its density, it is compatible with existing communication systems.

Such UWB technology is able to provide precise location recognition and tracking using a feature of occupying a very wide frequency band, attracting attention as a PHY of a location recognition WPAN system, and the location recognition service using the UWB technology is ubiquitous home. , Smart tag, lifesaving location tracking field, remote control, location recognition based on various control fields, body care monitoring and medical personnel that require the location of the medical staff.

In particular, the ubiquitous location-based service, which recognizes the location of people and objects and provides useful services based on them anytime, anywhere, has emerged as an important service.In March 2004, IEEE 802.15 Alternate Task Group aimed at location-based low-power PHY standards. (TG4a) was launched, and in May 2004 the technical specifications required for IEEE 802.15.4a standardization were published.

Standards related to WPAN are being promoted by IEEE 802.15. Among them, standards using UWB technology are IEEE 802.15.3a, a standard for high speed WPAN Alternate PHY, and IEEE 802.15.4a, a standard for low speed WPAN Alternate PHY.

However, the standard for high-speed UWB did not narrow the disagreement between MB-OFDM and DS-CDMA, and eventually decided to abandon international standardization and try to commercialize each. Therefore, the international standard for UWB was first established by IEEE 802.15.4a. It can be said.

IEEE 802.15.4a aims to establish a PHY that enables communication and distance measurement at the same time with low power consumption. UWB and Chirp Spread Spectrum technologies are adopted as the PHY of the low-speed location aware WPAN in IEEE 802.15.4a. .

Here, the chirped spread spectrum (hereinafter referred to simply as CSS) is a process of gaining a process gain by linearly sweeping the carrier frequency with time without using coding among modulation methods of spread spectrum communication. It is a way.

According to the present invention, in the ranging algorithm based on the IEEE 802.15.4a CSS description, the IEEE 802.15.4a CSS-based low configuration is configured to improve the ranging capability in an indoor environment and to process a plurality of signals at a time, compared to the conventional art. We propose a complexity ranging algorithm.

First, a description will be given of a conventional CSS-based ranging algorithm as follows.

In the delay calculation based on the IEEE 802.15.4a CSS wireless communication system, the k-th sub chirp is represented as follows through white Gaussian noise and multiple channels.

[Equation 1]

In Equation 1, m is an index of a path, d is a number of paths, an amplitude of the _mth path is a _m , a delay time of the _mth path is represented by τ _m , and n (t) is white. Represents Gaussian noise.

The delay time τ _m = P _int T _s + τ _{f, m} can be divided into P _int T _s , which is determined as the peak time point of the matched filter result, and τ _{f, m} less than the sampling interval.

At this time, de-chirped sub chirp as a pretreatment process for obtaining an accurate time of τ _{f, m} is obtained by the following [Formula 2].

[Equation 2]

In Equation 2 above, p is a sample index and Ts is a sampling interval, and each subfold consists of 38 samples, and the bandwidth for one subfold is 8.6875 MHz, but a rounded cosine window. Only about 22 samples are available by the raised cosine window.

Subsequently, a sinusoidal signal having delay information as a frequency component is obtained through a de-chirped subchirp, and the signal is separated into a signal and a noise space through singular value decomposition.

Subsequently, a delay time of each pass is obtained by using a subspace based algorithm such as Estimation of Signal Parameter via Rotation Invariant Technique (ESPRIT), Matrix Pencil (MP), etc. using Equation 3 below. .

[Equation 3]

However, in the conventional method as described above, since the distance measurement performance in the indoor environment is not satisfactory due to the multipath as described above, the following algorithm is provided in the present invention.

That is, the algorithm according to the present invention is based on the IEEE 802.15.4a chirp spread spectrum piconet 1, and thus the first and second subfolders of the symbol, or the third and fourth subfolders, that is, the time-frequency domain. Is an algorithm that calculates delay time through effective preprocessing with de-chirped subchirps of sublaps with the same slope in different bands.

Next, the details of the low complexity distance measuring method of the ultra-wideband wireless communication system according to the present invention will be described.

In the delay calculation algorithm, the first and second decubited subfolds of the IEEE 802.15.4a chirp spread spectrum piconet 1 can be expressed as the following [Equation 4] and [Equation 5].

[Equation 4]

[Equation 5]

[Equation 4] and [Equation 5] above show that the frequency information is the same and the phase information is different.

In addition, even when the above-described equations (4) and (5) are averaged, a signal including frequency information having original delay time information can be obtained.

In addition, as shown in the following [Formula 6],

[Equation 6]

In other words, comparing [Equation 6] with the decubed subcue signal before the preprocessing process, it can be seen that the signal has a desired frequency component, but the magnitude of the signal varies according to the delay time of the received path.

In addition, as shown in Figure 1, when the signal size of the path received through the pre-processing as described above, except for the path with the shortest delay, the signal of the path having a longer delay is canceled It can be seen that it has characteristics.

Therefore, by increasing the weight of the first-arrival-path, which is important information for distance calculation, the influence of multipaths other than the first reception path in the multipath environment can be reduced.

In addition, in calculating the delay time using the IEEE 802.15.4a chirp spread spectrum, if a delay time is calculated using a conventional algorithm for a full chirp, the subspace based algorithm must be applied four times. As described above, when the algorithm according to the present invention is used, the noise space based algorithm needs to be applied only two times.

This is because the computational complexity of the noise space based algorithm is high as O (N ³ ), which greatly reduces the complexity of the overall computation of the delay calculation algorithm.

Thus, according to the algorithm proposed by the present invention as described above, it enables a low complexity ranging algorithm.

Subsequently, the simulation results according to the algorithm proposed by the present invention as described above will be described.

The inventors of the present invention compared the root mean square error (RMS) of the conventional algorithm and the algorithm according to the present invention, respectively, in order to verify the effect of the above algorithm.

That is, as shown in Figures 2 and 3, the conventional Estimation of Signal Parameter via Rotation Invariant Technique (ESPRIT) algorithm using the chirp signals received in the low band and high band and their averaging and the algorithm according to the present invention Were compared respectively.

In addition, in Figs. 2 and 3, the conventional algorithm is shown as ConvAvg, ConvLB and ConvHB, where ConvLB and ConvHB respectively evaluate the results obtained from the subspace-based algorithm by using the substation in the low band and the high band. ConvAvg represents an evaluation result obtained by taking the average of ConvLB and ConvHB.

In FIG. 2, it is assumed that the integer delay is not zero, meaning that the dechipping point is n _int T _s away from the first arrival path.

In this case, the evaluation of the algorithm according to the present invention is almost the same as the conventional algorithm shown in FIG.

In a multipath channel with high delay, the suppression rate of the multipaths of the multipaths far from the initial arrival path is weak, while assuming that the delay is zero, as shown in FIG. Getting closer to

At this time, the algorithm according to the present invention, as shown in Figure 3, shows an improved result compared to the conventional algorithm for all the SNR intervals (SNR intervals).

That is, as described above, the algorithm according to the present invention cannot guarantee the improved result for all channels, but it can be seen that there is an improved effect for the small value delay.

In addition, since the algorithm according to the present invention requires only one subspace based processing using SVD or EVD, the processing can be simplified as compared to the conventional algorithm using separate subspace based processing.

As described above, the low complexity distance measuring method of the ultra-wideband wireless communication system according to the present invention has been described through the embodiments of the present invention. However, the present invention is not limited only to the contents described in the above embodiments. It is a matter of course that the present invention can be modified, changed, combined and replaced by a person skilled in the art according to the design needs and various other factors.

Claims (4)

IEEE 802.15.4a chirp spread spectrum based low complexity distance measurement used to calculate latency to measure distance in an IEEE 802.15.4a chirp spread spectrum based ultra wide band wireless communication system In the algorithm,
Obtaining sub chirp through white Gaussian noise and multichannel;
Obtaining a de-chirped sub chirp as a pretreatment process to obtain an accurate time;
Obtaining a sine signal having delay time information as a frequency component through the decued subfolder, and separating the sine signal into a signal and a subspace through singular value decomposition;
Thereafter, using the subspace based algorithm (SPR) such as Estimation of Signal Parameter via Rotation Invariant Technique (ESPRIT), Matrix Pencil (MP)
The preprocessing step has the same slope in the time-frequency domain, as in the first and second subfolds of the symbol or the third and fourth subfolds, based on IEEE 802.15.4a chirp spread spectrum piconet 1. Configured to reduce the complexity of the computation of the overall algorithm for calculating the delay time by obtaining the defolded subfold through a preprocessing process using the defolded subfolds of subbands of different bands and thereby calculating the delay time. A low complexity ranging algorithm based on an IEEE 802.15.4a chirp spread spectrum. The method of claim 1,
Obtaining the subfolder,
where m is the index of the path, d is the number of paths, the amplitude of the mth path is a _m , the delay time of the _mth path is τ _m , and n (t) is white Gaussian noise.
A low complexity distance measurement algorithm based on the IEEE 802.15.4a chirp spread spectrum, wherein the subchief is obtained using Equation 1 below.

[Formula 1]

The method of claim 1,
The calculating of the delay time may include obtaining the delay time using Equation 3 below.

[Equation 3]

The method of claim 1,
The pretreatment process,
When p is a sample index and Ts is a sampling interval, in the following [Formula 2],

[Formula 2]

IEEE 802.15.4a chirp Spread Spectrum Piconet 1, 2nd de-subfold the subfolder can be expressed as the following [Equation 4] and [Equation 5],

[Equation 4]

[Equation 5]

From the above [Equation 4] and [Equation 5], since the frequency information is the same and the phase information is different, the frequency information having the original delay time information is included even when the [Equation 4] and [Equation 5] are averaged. A low complexity distance measurement algorithm based on the IEEE 802.15.4a chirp spread spectrum, wherein the decubed subcue is obtained using Equation 6 below based on the signal obtained.

[Equation 6]

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