Wireless distance estimation with low-power standard components in wireless sensor nodes

In the context of increasing use of moving wireless sensor nodes the interest in localizing these nodes in their application environment is strongly rising. For many applications, it is necessary to know the exact position of the nodes in two- or three-dimensional space. Commonly used nodes use state-of-the-art transceivers like the CC430 from Texas Instruments with integrated signal strength measurement for this purpose. This has the disadvantage, that the signal strength measurement is strongly dependent on the orientation of the node through the antennas inhomogeneous radiation pattern as well as it has a small accuracy on long ranges. Also, the nodes overall attenuation and output power has to be calibrated and interference and multipath effects appear in closed environments. Another possibility to trilaterate the position of a sensor node is the time of flight measurement. This has the advantage, that the position can also be estimated on long ranges, where signal strength methods give only poor accuracy. In this paper we present an investigation of the suitability of the state-of-the-art transceiver CC430 for a system based on time of flight methods and give an overview of the optimal settings under various circumstances for the in-field application. For this investigation, the systematic and statistical errors in the time of flight measurements with the CC430 have been investigated under a multitude of parameters. Our basic system does not use any additional components but only the given standard hardware, which can be found on the Texas Instruments evaluation board for a CC430. Thus, it can be implemented on already existent sensor node networks by a simple software upgrade.Comment: 8 pages, Proceedings of the 14th Mechatronics Forum International Conference, Mechatronics 201

Simulation-Based Resilience Quantification of an Indoor Ultrasound Localization System in the Presence of Disruptions

Time difference of arrival (TDOA) based indoor ultrasound localization systems are prone to multiple disruptions and demand reliable, and resilient position accuracy during operation. In this challenging context, a missing link to evaluate the performance of such systems is a simulation approach to test their robustness in the presence of disruptions. This approach cannot only replace experiments in early phases of development but could also be used to study susceptibility, robustness, response, and recovery in case of disruptions. The paper presents a simulation framework for a TDOA-based indoor ultrasound localization system and ways to introduce different types of disruptions. This framework can be used to test the performance of TDOA-based localization algorithms in the presence of disruptions. Resilience quantification results are presented for representative disruptions. Based on these quantities, it is found that localization with arc-tangent cost function is approximately 30% more resilient than the linear cost function. The simulation approach is shown to apply to resilience engineering and can be used to increase the efficiency and quality of indoor localization methods

A Wireless Micro Inertial Measurement Unit (IMU)

In this paper, we present a wireless micro inertial measurement unit (IMU) with the smallest volume and weight requirements available at the moment. With a size of 22 mm x 14 mm x 4 mm (1.2 cm 3), this IMU provides full control over the data of a three-axis accelerometer, a three-axis gyroscope, and a three-axis magnetometer. It meets the design prerequisites of a space-saving design and eliminates the need of a hard-wired data communication while still being competitive with state-of-the-art commercially available MEMS IMUs. A CC430 microcontroller sends the collected raw data to a base station wirelessly with a maximum sensor sample rate of 640 samples per second. Thereby, the IMU performance is optimized by moving data post processing to the base station. This development offers important features in portable applications with their significant size and weight requirements. Due to its small size the IMU can be integrated into clothes or shoes for accurate position estimation in mobile applications and location-based services. We demonstrate the performance of the wireless micro IMU in a localization experiment where it is placed on a shoe for pedestrian tracking. With sensor data-fusion based on a Kalman filter combined with the Zero Velocity Update (ZUPT) we can precisely track a person in an indoor area

Passive indoor-localization using echoes of ultrasound signals

In this paper, we present our novel indoor-localization system. The system uses only short inaudible acoustic signals to locate acoustically passive objects in a room. Moving objects can be detected as well as resting objects. The localization device consists of a transmitter (speaker) and a multi-channel receiver with up to eight receivers (microphones). The total time-of-flight path from the speaker to the microphones is the round-trip-time of the signal from the speaker to the reflecting object and back to the microphones. Therefore, a localization algorithm is used to translate the timing into object coordinates. By using a simple approach of direct intersection, the 3D-coordinates of the reflecting surface of the target can be derived. In an experiment, we demonstrate the functionality of this approach

Acoustic Wake-Up Receivers for Home Automation Control Applications

Automated home applications are to ease the use of technology and devices around the house. Most of the electronic devices, like shutters or entertainment products (Hifi, TV and even WiFi), are constantly in a standby mode, where they consume a considerable amount of energy. The standby mode is necessary to react to commands triggered by the user, but the time the device spends in a standby mode is considered long. In our work, we present a receiver that is attached to home appliances that allows the devices to be activated while they are completely turned off in order to reduce the energy consumed in the standby mode. The receiver contains a low power wake-up module that reacts to an addressable acoustic 20-kHz sound signal that controls home devices that are connected to it. The acoustic wake-up signal can be sent by any kind of speaker that is available in commercial smartphones. The smartphones will operate as transmitters to the signals. Our wake-up receiver consists of two parts: a low power passive circuit connected to a wake-up chip microcontroller and an active micro-electromechanical system (MEMS) microphone that receives the acoustic signal. A duty cycle is required to reduce the power consumption of the receiver, because the signal reception occurs when the microphone is active. The current consumption was measured to be 15 μA in sleep mode and 140 μA in active mode. An average wake-up range of 10 m using a smartphone as a sender was achieved