We recently presented T-ROME a cross-layer routing protocol for wake-up receivers, along with a Markov chain based framework to model and analyze wake-up receiver based routing protocols. Using this analytical framework, we present here a modification to T-ROME that omits several messages but does not change the basic behavior of T-ROME. We analyze the performance of the modified algorithm and show that the modifications significantly reduce communication energy, time and overhead, especially in noisy environments. Furthermore we present a technique to prevent disconnected network nodes in cases where parent nodes die but preceding parent nodes are alive and in wake-up range.

The basic design of the traditional wake-up receiver implemented by different publications in the last few years is essentially based on a shared radio channel where a low frequency signal (which is modulated on a high frequency carrier, typically close to the 868 MHz ISM band) is transmitted. This signal is modulated using the OOK (On-Off Keying) scheme and later recovered by a passive demodulation circuit. Optionally, the signal may contain a variable length address in order to target selectively the goal nodes. In this new approach, a double wake-up channel is implemented instead of a single one. This is labeled as FSK (Frequency Shift Keying) wake-up receiver (FSK WuRx). Two complementary signals, modulated at different high frequency carriers are recovered and then conducted into a low power difference amplifier with adjustable gain. This component builds a differential wake-up signal that serves to stimulate an ultra-low-power wake-up IC. A proof of concept is carried out first using visible light communications. The resulting FSK WuRx was compared with published designs in the same field. Afterwards, a prototype of the FSK WuRx was constructed using off-the-shelf components. A sensitivity of -61 dBm was achieved by consuming approximately 11.7 μA. Interferer resilience analysis were also carried out and results were compared with an OOK WuRx. Values of the Carrier Interference Ratio (CIR) of -17 dB were achieved for in-band interferers and up to -39 dBm for interferes located in the middle of the two channels. Furthermore, a data rate of 8.1 kbps was obtained.

The reliability of an indoor localization system is often limited by the capability of the systems of distinguishing the line-of-sight signals in environments with multipath. Besides, estimating the height of the target can be challenging due to dilution of precision (DOP) and non line of sight (NLOS) situations. However, the reflections can be used to infer information about the scenario. We present a novel approach which exploits the ground reflections to reduce the error in three dimensional localization and detect reliably the line-of-sight signals. The presented approach uses the geometry of the reflections as the model of the RANSAC method. In this model, ground reflections and line of sight signals can be found just solving a quadratic equation, which reduces the computational power required compared to other approaches. The positions are estimated using local optimization algorithms. In real experiments, the median error in the height estimation was reduced from 25 cm to 4.2 cm.

Duty-cycled Medium Access Control (MAC) protocols certainly improve the energy efficiency of wireless networks. However, most of these protocols still suffer from severe degrees of overhearing and idle listening. These two issues prevent optimum energy usage, a crucial aspect in energy-constrained wireless networks such as wireless sensor networks (WSNs). Wake-up radio (WuR) systems drastically reduce these problems by completely switching off the nodes' microcontroller unit (MCU) and main radio transceiver until a secondary, extremely low-power receiver is triggered by a particular wireless transmission, the so called wake-up call. Unfortunately, most WuR studies focus on theoretical platforms and/or custom-built simulators. Both these factors reduce the associated usefulness of the obtained results. In this paper, we model and simulate a real, recent, and promising WuR hardware platform developed by the authors. The simulation model uses time and energy consumption values obtained in the laboratory and does not rely on custom-built simulation engines, but rather on the OMNET++ simulator. The performance of the WuR platform is compared to four of the most well-known and widely employed MAC protocols for WSN under three real-world network deployments. The paper demonstrates how the use of our WuR platform presents numerous benefits in several areas, from energy efficiency and latency to packet delivery ratio and applicability, and provides the essential information for serious consideration of switching duty-cycled MAC-based networks to WuR.

In this paper we present a novel indoor localization approach based on measuring the time of flight (TOF) of ultrasound signal reflections in human bodies and walls. This is a stand off detection approach, it does not require the user to carry any wireless device. Only a static co-located speaker and microphone pair is used. The speaker sends a chirp, which is reflected to the environment. Then, the microphone receives the chirp and the reflections, measuring the reception times. Subsequently, the position of the target is estimated by the line of sight signal and the second reflections from 2 walls. Fast normalized correlation is used to estimate the timestamps of the received signals. The human being reflections are detected by subtracting the correlated signal in consecutive intervals, exploiting the fact that even a static human being moves slightly due to his breathing. Besides, we use a polynomial approximation of the reflections to increase the accuracy of this process. The choice among the remaining peaks is done by minimizing the error of the geometrical equations involved. When the target is moving continuously, an unscented Kalman filter is used to predict the most reliable peaks and estimate the position of the target. Real measurements show the capability of the proposed approach of localizing a person standing still with a median error of 0.15m and a moving human being with a median error of 0.08m and a standard deviation of 0.13 m.

Indoor localization based on time difference of arrival (TDOA) has been recently a promising field of study. We consider the previously unsolved problem of locating a moving target receiver by using unsynchronized stationary beacons without requirement of manual calibration. Thus, the received signals and their time of arrival (TOA) have to be assigned to a beacon. Besides, in order to automatically calibrate the system it is required to estimate the time offsets between the senders, their positions and the initial receiver position. We present an approach to estimate all the variables of the scenario using the gradient descent and the Gauss-Newton method, two local optimization algorithms which use the derivative of a system of hyperbolic error equations. Besides, we present an ultrasound transmission system approach which fulfils the requirements of this scenario, being robust against multipath and estimating the reception time with high accuracy. In order to avoid interference by echoes the packet size is reduced by using two frequencies in Orthogonal Frequency Division Multiplex (OFDM). Further, the transmission system enables distinction of the beacons, as the ultrasound signals are used both for localization and for information transmission. The simulations show the local optimization algorithms are capable of estimating the positions of the beacons, receivers and offsets. They require only a rough knowledge of the sender positions. Further, real experiments show that the timestamps are measured with a standard deviation of only 1.19 μs for a SNR of 10 dB, which corresponds to standard deviation of about 0.4 mm for the distance measurement.

The main idea behind this project is to provide a unified platform which will cover a complete process for embedded systems learning. A modular approach is considered for skills practice through supporting individualization in learning. This platform shall facilitate a novel development of universal approach in creative learning environment and knowledge management that encourage use of ICT. New learning model is challenging the education of engineers in embedded systems design through real-time experiments that stimulate curiosity with ultimate goal to support students to understand and construct their personal conceptual knowledge based on experiments. In addition to the technological approach, the use of cognitive theories on how people learn will help students to achieve a stronger and smarter adaptation of the subject. Applied methodology will be evaluated from the scientific point of view in parallel with the implementation in order to feedback results to the R&D.

Localization based on the time difference of arrival (TDoA) has turned out to be a promising approach for indoor environments, especially in combination with innovative self-calibrating TDoA algorithms that eliminate the need to measure the positions of reference receivers. We consider the previously unsolved problem of locating a moving target receiver by discrete signals from stationary beacons at unknown locations. We assume that the beacons are small and inexpensive and they require no further communication, i.e. they are unsynchronized. They only emit short discrete signals at regular intervals, of which we assume that they can be distinguished. The moving target travels on an unknown trajectory, receiving signals from the beacons and calculating the TDoA of the signals. First, we discuss adaptions of two TDoA algorithms by which the senders can be located from unknown signals. Second, we propose two novel approaches based on probabilistic state estimation to enable robust localization of the mobile receiver using the discrete arrival times, once the senders have been located. The probabilistic algorithms use the particle filter and the unscented Kalman filter to estimate the position and velocity of the target, as well as the unknown synchronization offsets of the senders. We provide a motion model and a sensor model for which we take into account that the signals of the beacons are received as singles, each at a different time. We verify the feasibility and robustness of our approach in extensive simulations, where we analyze the reliability of localization and compare both algorithms.

The use of duty-cycling in Medium Access Control (MAC) protocols effectively helps improving the energy efficiency of wireless networks. However, while the benefits of these protocols are unquestionable, most of them still suffer from overhearing and idle listening, two issues that prevent duty-cycled systems from achieving optimum energy usage, which is a crucial aspect in specific types of wireless networks such as Wireless Sensor Networks (WSN).Wake-up Radio (WuR) systems have been employed recently to overcome these issues. Under this approach, the nodes' MicroController Unit (MCU) and main radio transceiver are completely switched off and only activated when a secondary, extremely low-power receiver in the node is triggered by a particular wireless transmission. Wake-up Radio systems allow for drastic energy savings since receiver nodes are only activated on-demand, maximizing their battery lifetimes. In this paper, we have modeled and simulated a real, recent and promising WuR hardware platform based on its time and energy consumption characterization. By comparing such WuR approach to B-MAC and IEEE 802.15.4, two well-known and widely employed MAC protocols, we show it effectively out-performs the conventional WSN MAC approaches in terms of energy efficiency. To the best of authors' knowledge, this is the first study to include a comparative analysis for multi-hop networks based on a real WuR platform, which shows WuR systems represent an energy-efficient solution that also provides a good tradeoff between latency, packet delivery ratio and applicability..

In this paper, we present a novel smartphone indoor localization system. The smartphone user is localized with small effort, affordable equipment and with high accuracy in indoor areas. The system uses commercially available smartphones generating high pitched acoustic chirp signals beyond the audible range. The chirp signals are received by sound receivers which identify the specific sound produced from each smartphone. The receivers are connected to a WiFi network, such that they synchronize their clocks and exchange the time differences of arrival (TDoA) of the received chirps. In this way, using an iterative multilateration algorithm, the location of the smartphones can be calculated and the receiver positions are calibrated automatically. For generating the specific sound signals from the smartphone and for user navigation an Android software application was developed. The user interface is simple and is invoked by starting the software application, which automatically connects to a server and receives an ID using the internet connection of the smartphone. Furthermore, the user is assigned specific parameters, such that several devices can be distinguished by the appearance of the chirps. The position of the user is displayed on the smartphone in context of the environment, with a map and surrounding items. In the presented work we have verified our system in a real-world scenario. We compared our trajectory of a pedestrian carrying smartphone to the reference positions. We could locate the smartphones with error margin of 30 cm. a centimeter margin of error.

Precise indoor localization of robots in intra-logistic areas is of significant value in modern production. For this scenario we developed a pure optical localization system, consisting of a laser scanner and numerous mobile tags mountable on robots. The scanner searches and follows the mobile tags in the production hall continually. The tags receive the laser beam and determine their position with respect to the scanner. By the solid angel of laser beam deflection (angle of arrival) and separate infrared communication the position is generated. The system is full multi-target capable at low price for each tag. Furthermore, the data are directly available on the mobile tag. In this paper we describe the key components and algorithms of our localization system. We measured the scanning performance and maximum range of the optic components to optimize the first prototype.

In this work we present a novel concept for the next generation intelligent wireless sensing application where a universal remote control is implemented to govern different electronic devices inside a room with least effort. The so called Wireless Access to Numerous Destinations (WAND)-Pointer is an electronic device with an integrated inertial and distance measurement unit. The WAND-Pointer identifies the specific target by aiming the pointer in the desired direction. The effort of selecting a specific device by pressing a switch button on a universal remote control is no longer necessary. The WAND-Pointer is an effective solution in scenarios where elderly people have identification problems when forced to handle numerous control devices.

We present an approach for the localization of passive receiver nodes in a communication network. In our settings the positions of the nodes are unknown. The only source of information is the time when environmental sound or ultrasound signals are received. The discrete signals occur at unknown positions and times, but they can be distinguished. The clocks of the receivers are synchronized, so the time differences of arrival (TDOA) of the signals can be computed. The goal is to determine the relative positions of all receiver nodes and implicitly the positions and times of the environmental signals. Our novel approach, the Iterative Cone Alignment algorithm, solves iteratively a non-linear optimization problem of time differences of arrival (TDOA) by a physical spring-mass simulation. Here, our algorithm shows a smaller tendency to get stuck in local minima than a non-linear least-squares approach. The approach is tested in numerous simulations and in a real-world setting where we demonstrate and evaluate a tracking system for a moving ultrasound beacon without the need to initially calibrate the positions of the receivers. Using our approach we estimate the trajectory of a moving model train with a precision in the range of centimeters.

This work proposes the use of magnetic coupling for powering autonomous sensors in space-constrained applications, such as occupancy and belt detection in removable vehicle seats. The power demand of the autonomous sensor is considered between tens and hundreds of milliwatts. A theoretical analysis first highlights the critical parameters in order to achieve a large powering range and high efficiency. Series-resonant tanks are considered for both the primary and secondary networks. Because the intended application is space-constrained, small coils have to be used. In order to increase their quality factor, commercial ferrite-core coils are used. A class D power amplifier is proposed for the primary network. Experimental results show that a power of tens of milliwatts can be transferred to a 100 §U load placed at the secondary network up to a distance of 2cm, near seven times the radius of the coils (3mm). The addition of a rectifier and a voltage regulator at the secondary network in order to properly power an autonomous sensor (3V@30mA) limits the powering range to 1cm. Overall power efficiencies around 45% and 20% are achieved respectively at distances of 5mm and 1cm.

Numerous investigations of mobile radio communication have been conducted in environments such as urban, outdoor-to-indoor or indoor, only a few are in ruins. Within a running project, I-LOV, a study of a mobile radio propagation channel in urban search and rescue scenarios is conducted. Due to complex environment in ruins, great multipath interference can take place, which strongly impacts communication quality and localization accuracy. This paper focuses on the characterization of time dispersion in such scenarios at GSM 900, GSM 1800 and UMTS frequency bands. High resolution measurements have been performed under collapsed buildings and post-processing data analysis were executed. The mean delay and RMS delay spread has been investigated according to power delay profiles. The effect of frequency window function on impulse responses and delay spread is also researched.

In recent years, autonomous miniature airships have gained increased interest in the robotics community. This is due to their ability to move safely and hover for extended periods of time. The major constraints of miniature airships come from their limited payload which introduces substantial constraints on their perceptional capabilities. In this paper, we consider the problem of localizing a miniature blimp with lightweight ultrasound sensors. Since the opening angle of the sound cone emitted by a sonar sensor depends on the diameter of the membrane, small-size sonar devices introduce the problem of high uncertainty about which object has been perceived. We present a novel sensor model for ultrasound sensors with large opening angles that allows an autonomous blimp to robustly localize itself in a known environment using Monte Carlo localization. As we demonstrate in experiments with a real blimp, our novel sensor model outperforms a popular sensor model that has in the past been shown to work reliably on wheeled platforms.

This paper presents two adaptive recursive tracking techniques for precisely localizing a mobile vehicle in an indoor industrial environment. An Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF), the corresponding algorithms and mathematical models are presented and analysed. Experimental range measurements generated from local positioning radar system are used to test the performance of these algorithms with respect to position and velocity root mean square errors. True and estimated trajectories of the mobile vehicle with associated means and error covariances are illustrated with the number of samples required in each case. Results obtained show that UKF outer performs EKF with respect to positioning accuracy and root mean square error. Both filters show comparable computational complexity with more robustness obtained by applying UKF for non linear estimation since there are no linearization errors as in the case of EKF.

The main applications of surface acoustic wave (SAW) convolvers have previously been military and have required high processing gain values. Rather complex hybrid fabrication technologies have to be employed needing large packages and resulting in expensive devices. Applications in radio frequency (RF) consumer communications use relatively short code sequences. For these systems, low-cost SAW convolvers with moderate time-bandwidth products on the order of a few hundred have many interesting features. To meet the demands for low price and high reliability, precise reproducible designs and economic mass production of the devices are indispensable. The authors report on the design and performance of a small and compact prototype SAW convolver. Input center frequency, integration time and time-bandwidth product are 350 MHz, 3 /spl mu/s and 150, respectively.