Yunzhou Zhang

A Survey of Localization in Wireless Sensor Network

Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network.

Indoor robot localization based on wireless sensor networks

An effective indoor localization method of hybrid RSSI/TDOA is proposed to reduce the big errors occurred during indoor RSSI localization and high cost paid by TDOA localization. It measures RSSI with iterative recursive weighted average filter, and polynomial model is obtained to fitting the RSSI measurement and to obtain polynomial model. Furthermore the hybrid RSSI/TDOA localization algorithm is employed. The experiment results show that the proposed method of iterative recursive weighted average filter will improve the accuracy of RSSI localization on the condition of lower computation complexity, and the achieved localization is more accurate in the polynomial fitting than in the log-normal shadowing model. Moreover, the indoor location accuracy in the experiment is approximate 0.5 meter that satisfies the precision requirement of indoors location precision.

An Indoor Localization Strategy for a Mini-UAV in the Presence of Obstacles

In this paper, we propose a novel approach to mini-UAV localization in a wireless sensor network. We firstly employ the environment adaptive RSS parameters estimation method to estimate the parameters of range estimation model. However, the direct path from the target to a beacon is blocked by obstacles in a complicated indoor environment. So the proposed method, which employs a sequential probability ratio test to identify whether the measurement contains non-line of sight (NLOS) errors, is tolerant to parameter fluctuations. Finally, a particle swarm optimization-based method is proposed to solve the established objective function. Simulation results show that the proposed method achieved relatively higher localization accuracy. In addition, the performance analyses, carried out for a realistic indoor environment, shows that the proposed method still preserves the same localization accuracy.

Design and research of digital meter identifier based on image and wireless communication

Based on image recognition and wireless shortrange transmission, we designed and implemented a kind of equipment to identify the value of several digital domestic instruments such as kilowatt-hour meter and gas meter. CMOS image sensor is used to form focused image of the meter reading. Then, the digital image is processed by a high-performance DSP processor with advanced neural network algorithm. The identification result is specific numbers and is sent to the concentrator through the shortrange wireless ZigBee communications. The equipment can effectively release the workers from entering residential buildings and avoid many troubles.

Indoor Mobile Localization in Wireless Sensor Network under Unknown NLOS Errors

Localization is one of the key techniques in wireless sensor network. One of the main problems in indoor mobile localization is non-line-of-sight (NLOS) propagation. And the NLOS effects will lead to a large localization error. So the NLOS problem is the biggest challenge for accurate mobile location estimation in WSN. In this paper, we propose a likelihood matrix correction based mixed Kalman and H-infinity filter (LC-MKHF) method. A likelihood matrix based correction method is firstly proposed to correct the LOS and NLOS measurements. This method does not need the prior information about the statistical properties of the NLOS errors. So it is independent of the physical measurement ways. And then a mixed Kalman and H-infinity filter method is proposed to improve the range measurement. Simulation results show that the LC-MKHF algorithm has higher estimate accuracy in comparison with no-filter, Kalman filter, and H-infinity filter methods. And it is robust to the NLOS errors.

Research of automatic recognition of digital meter reading based on intelligent image processing

With the rapid development of intelligent building, the requirement of automatic recognition of digital meter reading is increasingly urgent. Based on image processing, this article uses iterative global threshold to binarize the images and then adopts projection method to locate the target regions and divide the numbers. Features are extracted and back-propagation neural network is used to read the numbers automatically and contributes to a high accuracy of recognition rate.

A coordinated control strategy for stable walking of biped robot with heterogeneous legs

Purpose – The purpose of this paper is to present a coordinated control strategy for stable walking of biped robot with heterogeneous legs (BRHL), which consists of artificial leg (AL) and intelligent bionic leg (IBL).Design/methodology/approach – The original concentrated control in common biped robot system is replaced by a master‐slave dual‐leg coordinated control. P‐type open/closed‐loop iterative learning control is used to realize the time‐varying gait tracking for IBL to AL.Findings – The new control architecture can simplify gait planning scheme of BRHL system with complicated closed‐chain mechanism and mixed driving mode.Research limitations/implications – Designing and constructing a suitable magneto‐rheological damper can greatly improve the control performance of IBL.Practical implications – Master‐slave coordination strategy is suitable for BRHL stable walking control.Originality/value – The concepts and methods of dual‐leg coordination have not been explicitly proposed in single biped robot ...

Multi-resolution optical flow tracking algorithm based on multi-scale Harris corner points feature

Multi-resolution optical flow tracking algorithm decomposes the object displacement in the wavelet pyramid, then sparse optical flow based on LK (Lucas-Kanade) algorithm matches the object feature in all the level of the wavelet pyramid step by step. Steadily tracking rapid motion objects is achieved. As to the feature of motion vehicles, multi-scale Harris corner detection based on wavelet is proposed. Traditional Harris corner detection about omitting corner point and asymmetrical array is improved. It is suitable to extract motion vehicle feature in complicated traffic scene. With the experiment, it can be verified that the corner point is always steady and reliable when the vehicle is turning and moving, and the camera is zooming in and out. The tracking algorithm also can accurately match the feature points with the high real-time performance.

Research of an energy-aware MAC protocol in Wireless Sensor Network

Because of the manner of wireless communication channel and limited communication resource, research of MAC protocol is one of challenging issues in Wireless Sensor Network (WSN). S-MAC is a representative MAC protocol for Wireless Sensor Network, but its energy strategy is still not perfect. Focus on energy efficiency, a new S-MAC based protocol that is called Packets Decision MAC (PD-MAC) is proposed. In PD-MAC, data-based RTS/ CTS is designed to bring forth details of data packets to all neighbor nodes. Based on these details, packets decision scenario is proposed to help neighbor nodes selectively abandon the right of packets transmission. So the amount of transmitted packets and probability of collision can be reduced reasonably, and energy consumption on them will be saved. With the simulations, the proposed protocol is evaluated in comparison with S-MAC from energy efficiency to accuracy of packets received by sink The performance of PD-MAC is verified to be efficient and competent.

A rescue-assist wireless sensor networks for large building

This article designs a rescue-assist wireless sensor networks for fire rescue and health care in large building. This system consists of wearable tags, route sensor nodes and base station. The wearable tag detects the activity of the user. We firstly propose an efficient fall detection algorithm. This algorithm has a low computational complexity and can be used in sensor node. And the wearable tag sends emergency information to the base station when the user is detected falling down and cannot get up in a given time. And then we propose a localization method to locate the user in NLOS environment. This method removes the NLOS effects through a NLOS identification algorithm to improve the localization accuracy. The system and proposed algorithms have been put into actual test application, the experimental results demonstrate that the system is able to apply in rescue and the localization algorithm can locate the user accurately in the building.