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With the development of wireless communication technology, in the 21st century, the world is entering the era of wireless Internet from the Internet age. Emerging wireless network technologies have been widely used wireless network-based positioning technology in offices, homes, factories, parks and other public aspects of life, such as WiFi, WiMax, ZigBee, Bluetooth and Ultra-wideband (UWB).
In the fields of outdoor positioning, the global position system (GPS) is already available with limitations in the accuracy and is mainly for movement localization, such as ships, automobiles, and aircraft and other moving objects position and navigation. In addition to the GPS applications in navigation and outdoor environments positioning, indoor localization has brought general attention to people. In the future, the trend of wireless localization technology is to combine indoor positioning with outdoor positioning to achieve a seamless and accurate positioning.
Due to the numerous of advantages of UWB technology, the indoor localization based on UWB stands out in many wireless location technologies .
High accuracy indoor localization is becoming more popular and important since GPS is not satisfied indoor environment, because of its limitations. For example, owing to low penetration of signal of GPS, the accuracy of GPS has low estimation accuracy in indoor conditions; even users cannot detect any signals. Therefore, to find a suitable approach to solve this problem is imminent. This project is aim to employ an approach to achieve the demands of high accuracy indoor localization, which combines multiple input and multiple output (MIMO) technologies and indoor localization based on UWB impulse radio technologies.
In this research, the following objectives will be achieved:
A) To familiar the knowledge of indoor localization and relevant positioning estimation algorithms.
B) To Study UWB schemes and search a method to use UWB for positioning at indoor environments.
C) To design a system for indoor localization based on UWB technology to improve the accuracy of range estimation.
D) To build up a hardware model board of the system.
Chapter 2 Literature Review
2.1 Position Estimation for UWB Localization
At present, the impact of multipath is the most difficult and urgent aspect to be resolved in the issue of indoor location. In order to restrain this problem, the duration of positioning signal must be short for indoor environment, which will lead the energy of this signal very low .
Different approaches could be employed to solve the problem of localization, which base on UWB signals traveling among the target and some reference nodes. Generally, a possible position estimation includes two steps  . The first step is to measure the range between target and reference nodes. The second step is to estimate the position of target depend upon distance measured in the first step . There are two systems named "Self-positioning System" and "remote-positioning System (Network-centric positioning)", which whether based on the target position is estimated by the node itself or central unit . As shown in Figure 1 and Figure 2.
Figure Two-step positioning in a Self-positioning System 
From Figure 1, in the self-positioning system, firstly, the position of target is estimated by the related parameters depending upon received signals which come from the reference nodes, next is to estimate its position through these estimated parameters.
Figure Two-step positioning in a remote positioning system 
From Figure 2, in the remote positioning system, position related parameter estimation is based on the position signals of reference nodes. Then, these positioning related parameters are sent to the central unit which is utilized to estimate the position of target.
2.2 Algorithms of Position Estimation
The main effects on position estimation are from noise, multipath components and different transmission speeds through objectives under non-line-of-sight (NLOS) conditions . The common algorithms of position estimation are: Angles of Arrival (AOA), Received Signals Strength Indication (RSSI), Time of Arrival (TOA) and Time Difference of Arrival (TDOA).
2.2.1 Angles of Arrival (AOA)
The AOA measurement is to detect the location of target node by determining the direction of arrival radio signals of each antenna in the antenna array. The direction of the signal is determined by the TDOA of each the antenna reception signals . In the case of narrowband signals, the TDOA is phase shift of the arrival signals . The different arrival angles can be evaluated through combining the phase shift of the signals at receiver side so as to obtain AOA .
2.2.2 Received Signals Strength Indication (RSSI)
RSSI is to estimate the position of target according to the relationship between the received signals strength and signal propagation distance, based on the signal propagation model . However, this method is dependent on the channel transmission model in a large extent. Therefore, many elements can affect the performance of RSS range estimate. For instance, multipath or the changes of environmental conditions would lead distance estimation accuracy to be a serious deterioration. The advantage of UWB techniques will not be used widely.
Commonly, RSSI and AOA algorithms generally could not be employed alone for UWB positioning, they are just as primary adjunct for probably positioning.
2.2.3 Time of Arrival (TOA)
One of the most popular positioning techniques is TOA which detects the direct path (DP) in a multipath environment . TOA parameter provides estimation about the distance between target and reference nodes. There are two situations should be discussed. Firstly, when these nodes are synchronized, the TOA of the UWB signal can be employed to get an estimation range. Secondly, when these nodes are not synchronized, for the purpose of obtaining an estimated rang, the nodes can share the information of TOA by some specific protocols such as "two-way ranging" protocol .
Researchers general use a Cramer-Rao lower bound (CRLB) to access positioning estimation . The formula  is shown as following (1).
where stands for TOA and is bandwidth . Therefore, from (1), the accuracy is associated with Signal to Noise Ratio (SNR) and the effective bandwidth.
2.2.4 Time Difference of Arrival (TDOA)
The time difference of arrival (TDOA) estimation is employed to achieve the range information from the reference nodes when they are synchronized . TDOA is only measured difference of traveling time, which depends on hyperbolic cross to estimate the range between the target and reference nodes as shown Figure 3.
Figure TDOA Positioning Algorithm 
The basic principle of TDOA is that two different speed signals are transmitted by transmitter simultaneously to target node, and then compare the pair of signals' arrival time at the reception point. The distance of the reference node and the receiver could be calculated based on the arrival time difference of two signals. This method only needs to maintain synchronization between the reference nodes and target, while the strict time synchronization is not required in TOA .
Chapter 3 Specification
There are many wireless localization technologies and solutions, and the commonly used positioning technologies include infrared, ultrasonic, and Radio Frequency (RF) signal. However, these technologies are not suitable for indoor positioning. Limitations of infrared exist on the precise positioning, which is not only suitable for short-distance transmission, but also could easily be affected by the fluorescent lights in the room. Ultrasonic is greatly interfered by environmental conditions, such as multipath and non-line-of-sight (NLOS) propagation. Therefore, ultrasonic still could not be employed in the indoor environments. RF signal is usually used in outdoor positioning system. Similarly, if RF is adopted in indoor positioning, there also has interference, thereby reducing accuracy of positioning. 
Thus, with the increasing demands of the development of positioning technology and location-based services, wireless location technologies must meet the several conditions including high anti-jamming capability, high-precision positioning, information security and low-power and low-emission power . Obviously, the above technical solutions cannot fully meet these requirements. Wireless positioning based on UWB can basically satisfy the above requirements, due to high-speed, low-cost and low-power.
3.1 The Advantages of UWB
(a) Transmit power is low; the confidentiality of communications is good and spectrum efficiency is high. As ultra-wideband radio frequency bandwidth can reach up to 1GHz, the spectral density of signal power is very low. On the one hand, the UWB signal cannot easily be intercepted, and the confidentiality of the system performance has been improved. On the other hand, UWB system and the existing narrowband communication systems with same band can maintain good coexistence, which increase the effective of spectrum.
(b) High transmission rate, channel capacity. According to Shannon channel capacity formula (2), the increase of bandwidth means the significantly increase of channel capacity .
Where W is the bandwidth of the channel in Hz, S/N represents the signal to noise ratio.
(c) Good ability of anti-multipath. Due to the UWB transmitter signal using narrow pulses with very short duration, the multipath signals of narrow pulses are not easy to overlap in time domain. Thus, the receiver of the UWB system can detect multipath signals by adopting diversity techniques .
(d) Strong penetrating. As the low-frequency components is long-wave which contained in the UWB spectrum, ultra-wideband signal can penetrate a variety of materials, such as walls, which is suitable for the communication systems applied in the need of penetration capacity .
3.2 Effects Elements on Positioning Accuracy and Improvement
There are many factors that affect the wireless positioning accuracy, including multi-path effect, NLOS propagation and multiple accesses. In addition, the amount and layout of the positioning stations and transmitted signal parameters also could affect the positioning accuracy.
3.2.1 Multipath Propagation
In the multipath environments, the signal reaches to the receiver through multiple signal paths, as shown in Figure 4. Due to high time resolution of impulses of UWB, these impulses will be resolvable at receiver side, which can cause inaccurate TOA estimation. However, in order to gain accurate estimation, the direct-path detection algorithm could be adopted for UWB systems .
Figure A) Received Signal in a Single-path Channel
B) Received Signal over a Multipath Channel
(Source from )
3.2.2 NLOS Transmission
In the indoor environments, the signals transmission is very difficult between base station (BS) and the target in line-of-sight (LOS) propagation. When there is no direct path between target node and BS, the signal through obstacles will cause some time delay . Thus, there is a certain deviation of the first arrival time of the impulse with the true TOA value. In order to improve the accuracy of positioning in NLOS environments, mapping techniques  can be utilized.
3.2.3 Multiple Accesses Interference
In multi-user environments, the BS does not only receive the signals from target, but also from other devices. The interference between these signals would affect the positioning estimation, which reduces the ranging accuracy. Usually, in order to mitigate the influences of multiple accesses interference, each user can be assigned different time slots for the transmission. In addition, direct sequence spread spectrum can also be used to improve the anti-jamming performance of the system in the multi-user environment . There are other various techniques to mitigate the effects of interference, such as training sequence  and non-linear filtering .
Chapter 4 Technical Approach and Risk Analysis
There are many ways could be employed to estimate the location of target in wireless technologies discussed above, such AOA, TOA, RSSI. For indoor positioning applications, the TDOA will be chosen as the range estimation in this project. Firstly, since TDOA does not need to synchronize the reference nodes and target node. Additionally, the high time resolution of UWB can provide high accuracy of TDOA estimation.
Due to the IR waves transmit with constant speed rate in environment, the distance between the base station and the receiver is in direct proportion to the signals propagation time. The TDOA algorithm estimates the possible position of the target node by detecting the difference in arrival time of the same signal from multiple reference nodes. Every TDOA measurement should determine that the target node must be put in a hyperboloid with constant difference of the distance between two reference nodes , as shown in Figure 5. The location of the target is provided by the intersection of hyperbola.
Figure TDOA Estimation Algorithm 
In the two-dimensional (2D) plane, the ranges are difference from the target node (T) to each reference nodes (A, B, C), and the propagation time to A, B, C is difference as well from T. The difference of T to A and C is expressed as:
When the location of T is fixedï¼Œthe distance difference d can be derived. Therefore, an equation about and can be gained, and then the hyperbola can be determined. According to the signal arrival time difference from T to A and B, another hyperbola can be determined. The intersection of the two hyperbolas is the position of the target node T.
Generally, the target location is detected by a least squares algorithm to linearize the TDOA equation. The common approach for linearization is to employ Taylor Series Expansion, which has two significant disadvantages: it needs a good initial estimate and cannot guarantee convergence . However, the initialization and convergence problems can be eliminated by Two-Stage Weighted Least Square Solution algorithm .
Chapter 5 Task Definition
TASK 1: Background investigation of indoor localization, relevant knowledge of UWB and algorithms of indoor positioning
TASK 2: Background and in-depth study of indoor localization based on UWB, TDOA technology, improvement of accuracy of positioning, the effects on accuracy of positioning.
TASK 3: System design. Through the suitable approach (TDOA) to design the system of indoor localization based UWB. In addition, tracking simulation is carried out.
TASK 4: Get the simulated results and compare with theoretical results. To improve the performance of the system depending upon the simulated results.
TASK 5: Building up the hardware board. After simulation, to design the circuit and use the relevant components to build up an board used for indoor localization.
TASK 6: writing dissertation and submission.