- Research Article
- Open Access
Novel Received Signal Strength-Based Indoor Location System: Development and Testing
© Yuri Álvarez et al. 2010
Received: 29 January 2010
Accepted: 13 July 2010
Published: 15 August 2010
A received signal strength- (RSS-)based indoor location method (ILS) for person/assets location in indoor scenarios is presented in this paper. Theoretical bases of the method are the integral equations relating the electromagnetic (EM) fields with their sources, establishing a cost function relating the measured field at the receivers and the unknown position of the transmitter. The aim is to improve the EM characterization of the scenario yielding in a more accurate indoor location method. Regarding network infrastructure implementation, a set of receivers are deployed through the coverage area, measuring the RSS value from a transmitter node which is attached to the asset to be located. The location method is evaluated in several indoor scenarios using portable measurement equipment. The next step has been the network hardware implementation using a wireless sensor network: for this purpose, ZigBee nodes have been selected. Finally, RSS measurements variability due to multipath effects and nonline-of-sight between transmitter and receiver nodes is mitigated using calibration and a correction based on the difference between the free space field decay law and the measured RSS.
A great amount of research has been carried out for many years about the problem of location estimation due to its enormous importance for many engineering fields. The growth of short-range wireless communication networks, both for personal or industrial purposes, as well as the compatibility between network devices (WiFi-certified), has contributed to the development of radiodetermination methods for indoor environments. Different wireless networking techniques have been proposed as infrastructure : for example, IrDA [2–4], WLAN [5, 6], Bluetooth , Ultra Wide-Band (UWB) [8–10], and ZigBee .
Signal reflection in the obstacles, that supposes multipath contributions in the radio-frequency (RF) location system sensors.
Signal attenuation when passing through the obstacles placed between the RF transmitters (Tx) and receivers (Rx) .
The noise level, that may seriously affect the system performance. It may be critical in ILS due to the low emitted power regarding battery savings in the location network nodes.
The presence of other devices working at the same frequency band may interfere with the sensor network.
Concerning ILS design, it will be influenced by various application requirements such as location network scalability, energy efficiency, and location accuracy .
time-of-fly (ToF) methods, based on the signal propagation time between the Tx and Rx nodes. ToF methods include: time-of-arrival (ToA), time-difference-of-arrival (TDoA),
angle-of-arrival (AoA) techniques, where the position is estimated by means of the knowledge of the direction of arrival of the signal in the receivers,
received signal strength (RSS) methods, which are founded on the decay law of the received signal versus the distance.
ToA and TDoA methods require the use of ultra wide-band (UWB) devices in order to achieve enough temporal resolution, so that the echoes corresponding to reflected signals can be identified and suppressed [8–10]. There are some distinctive advantages of short-range UWB: high immunity to interference from other radio systems, high multipath immunity, high data rate, and accurate resolution capability. Despite UWB methods are more accurate than those ones based on RSS measurements, the network infrastructure is more expensive .
Apart from being technically less complex (and hence, less expensive), another advantage of RSS methods with respect to ToF ones is the possibility of using existing wireless infrastructures, for example, WLAN access points [5, 6]. However, RSS methods accuracy is limited by the signal level fluctuations due to multipath contributions that occur in indoor scenarios. Moreover, it must be taken into account that most of the existing wireless devices (e.g., WLAN access points, ZigBee nodes, etc.) have not been designed for an accurate RSS measurement, increasing the measured values uncertainty.
With regards to the indoor scenario's characteristics, the presence of obstacles and walls may obstruct the line-of-sight (LOS) between location network nodes. Some of the mentioned ILSs are often designed to work at frequency bands where LOS between the transmitter and the receiver is required. Then, a high number of receivers and repeaters is typically necessary to ensure the LOS condition . This requirement comes from the signal attenuation effect when passing through objects and walls , as well as the need of compensating the measurements distortion due to multipath effects on each network node.
In this sense, it is necessary to remark that, according to a comparison between commercially available sensor nodes supporting TDoA and RSS , RSS-based methods can be advantageous in a crowded area where the direct links between a target node and reference nodes are frequently shadowed by walking people. Thus, an RSS method would be enough to fulfill the location requirements depending on the requested accuracy.
The following contribution describes an RSS-based indoor location method for assets location and tracking in industrial warehouses. The method must fulfill an accuracy requirement which is around 5% of the indoor scenario's size. The location algorithm, it is based on the establishment of a cost function having the electric field measurements in a set of Rx as inputs, and being the unknown the Tx node position. This Tx node will be attached to the asset to be located/tracked. Aiming to improve the method accuracy, which is limited by the use of a free-space field propagation model, multicarrier information can be considered.
Regarding hardware infrastructure, ZigBee, a new industrial standard for ad hoc networks based on IEEE 802.15.04 PHY and MAC , has been chosen due to its features which makes it suitable for low data rate, low power, and cost-effective wirelessly networked products. Expected applications for ZigBee include remote monitoring, home control, industrial automation, and localization.
proposal of a new model relating measured RSS values and free-space field decay law that takes into account the near field terms,
combination of multifrequency information, subject to the hardware infrastructure capabilities (e.g., the selected ZigBee nodes do not support this feature),
scenario division in cells, collecting RSS information in a central point inside each cell. These RSS values are used to calibrate the proposed location method.
2. Description of the Method
2.1. Electromagnetic Propagation Model
where is the field (or signal) level at the Tx node, the field level at the is the wavelength and is the Tx-Rx distance .
Equation (1) supposes free-space and far-field conditions. Sometimes, due to the working frequency and the Tx-Rx distance (R), near-field terms (field decaying as and ) should be taken into account to avoid loss of accuracy.
Theoretically, (1) and (2) are valid for free-space conditions. However, it will be shown that they still provide accurate location results in moderate multipath environments.
2.2. Tx Position Determination
where MEAS is the amplitude of the measured electric field at each Rx for each carrier The cost function is established as the difference between the measured value and the evaluation of (2) at different positions inside the indoor scenario (EST term). is the number of Rx nodes, and is the number of carriers.
The cost function defined in (3) is nonlinear with respect to the unknowns being suitable to be solved using nonlinear optimization techniques (Newton-Raphson , Levenberg-Marquardt ). However, RSS measurements are affected by multipath effects or attenuation when passing through walls, distorting them from the expected free space values. The result is that the cost function may have local minima, where the mentioned minimization methods  can be trapped.
Taking into account these aspects, it is proposed a cost function minimization based on a best-effort method: the domain is divided using a grid; the cost function is evaluated at each point of the grid the Tx position estimation corresponds to the point where the cost function has the lowest value [24, 25].
2.3. Location Method Calibration
The value appearing in (1) and (2) will be determined in order to avoid inaccurate location results. In addition, different characteristics of the nodes should be taken into account: the use of a unique value for all the Rx nodes supposes that all of them have the same characteristics (e.g., antenna radiation pattern, radiation efficiency, and antenna adaptation).
The coverage area is subdivided in several cells (see Figure 12), whose size should not be larger than 4-5 m, reducing the possibility of RSS values corruption when multipath contributions become as significant as the direct contribution (see Figure 5).
The Tx node is placed inside each cell (position denoted as calibration point, see Figure 12), obtaining a set of RSS measurements.
Being known the Tx position (calibration point coordinates), the measured RSS values on each cell are used to determine a calibration coefficient (CC) for each Rx node and for each cell. The CC's values are proportional to the RSS value deviation with respect to the free space field decay law (see Figure 2).
The described calibration procedure can be seen as a rough fingerprinting technique, as the one described in . Fingerprinting is based on measuring the RSS values in all the points of a grid which covers the ILS deployment area. The method described uses the calibration to reduce the measured RSS values deviation with respect to the free space field decay law. Moreover, the calibration procedure corrects the differences between the location network sensors (antenna gain and adaptation as well as the receivers' sensitivity).
3. Experimental Validation
The proposed RSS-based indoor location method was first evaluated using simulation tools for the prediction of radioelectric coverage in indoor scenarios, as explained in . The next step has been experimental validation using a set of indoor measurements.
Regarding the working frequency band, two ISM (industrial, scientific, and medical) bands have been selected: 433 MHz and 2.4 GHz (being the last one coincident with ZigBee devices), and the 868 MHz frequency, which is used for RFID applications and short-range RF communications. It is expected that accurate results will occur for the lowest frequency (433 MHz), as the attenuation and multipath effects increase with the frequency.
First, the proposed free-space model is compared with simulations and measurements. Figure 5 shows the field level along the -axis being = 2450 MHz. Measurements have been done each = 10 cm (0.8 ). It is possible to appreciate a good agreement with the free-space field decay law for those positions close to the Tx position ( 3 m). For larger distances ( 3 m), effects of multipath due to reflections in floor and walls appear as fast oscillations on the measured field level.
LOS and NLOS accuracy comparison.
Averaged error (m)
Mean value of each col.
To conclude this section, it must be remarked that the measurement setup presented in this section is conceived to provide accurate RSS measurements, so inaccuracies are mainly due to indoor propagation effects (signal attenuation, multipath).
4. ZigBee Implementation
4.1. ZigBee Network Description
Once the proposed RSS indoor location method has been evaluated in real indoor scenarios, a testbed based on a ZigBee network is proposed. The network uses three node types all based on the same 802.15.4 PHY link: a gateway or coordinator node used to interface the ZigBee Network and computer controller, a number of static nodes at known locations and the mobile node attached to the mobile asset. Background coverage for the network is provided by the static nodes, which are located throughout the target area, on a grid of roughly 20 to 30 meters, which gives a minimum coverage network for a building or area.
ZigBee standard  requires RSS indication to be measured accurately for general channel assessment. The interchangeable modules XBee and XBee-PRO  from MaxStream are selected because these chips provide RSS indication measurement tagged to a specific packet. The operating frequency is 2.4 GHz, with a 250 Kbps data rate. XBee module provides up to 30 m ranges for indoor and urban environments and up to 100 m for LOS outdoor conditions (with dipole antennas), both for a 1 mW (0 dBm) output transmitted power whereas XBee-PRO module provides, for a 100 mW (20 dBm) output transmitted power, up to 100 m ranges for indoor and urban environments and up to 1200 m for LOS outdoor conditions (with dipole antennas). The method presented in this contribution takes into account the XBee or XBee-PRO features in order to equalize the RSS value. The ZigBee modules are configured to operate in the application programming interface (API) mode, allowing that a host application can configure the modules and interact with their networking capabilities. Concerning software configuration, the static nodes or beacons (Rx nodes) are set as Reduced Function Devices (RFD), and the mobile node (Tx node) is configured as a Full Function Device (FFD).
4.2. ZigBee Nodes Simulation
Prior to the ZigBee-based location network implementation, the proposed location method's performance using simulated RSS values has been evaluated.
The ZigBee nodes' limitation with respect to the measurement setup described in Section 3 is that just one frequency (2.45 GHz) is available, being not possible the use of multifrequency information to increase the location method's accuracy. In consequence, the strategy to be adopted in this section will be the scenario division in cells. For this example, two cells of approximately 5 m 4 m are considered, being the calibration points' coordinates listed in Table 3. Cells' sizes and calibration points are plotted in Figure 11.
A new set of RSS measurements is calculated each 1 second in all the Rx.
Next, the method estimates the cell (Cell 1 or Cell 2) where the Tx is placed, by looking at the highest RSS values in all the Rx.
RSS measurements are used to compute the cost function, weighting them by the CC's of each Rx node.
The cost function is minimized and the Tx position is estimated, determining again the RSS values deviation with respect to the free space decay law (see Figure 2).
The Tx position is estimated using the RSS values corresponding to the nondiscarded nodes.
At this point it is important to remark again the idea of the scenario division in cells. Apart from the calibration considerations mentioned at the end of Section 2.3, the goal of the cells is to reduce the area where the cost function is evaluated, as illustrated in Figure 12.
The method's accuracy has been tested in two different positions: Position 1 is = 3 m, = 3 m (green point in Figure 12), and Position 2, = 1.75 m, = 3 m (purple point). Multipath effects and nonstationary conditions of the indoor environment are simulated by adding noise to the simulated RSS values. The signal-to-noise ratio (SNR) is defined at the distance of 1 m from the Tx (free-space field decay law at 1 m, and the effects of the noise in the RSS values are shown in Figure 2).
4.3. Measurement Setup
A full-wave-based indoor location method has been presented. The proposed technique has been tested in different real indoor scenarios, analyzing the free-space model accuracy in multipath environments. First, an accurate measurement setup was proposed, checking the method's capabilities for handling multifrequency RSS information, yielding in a more accurate Tx position estimation. Next, the ZigBee-based sensor network was used regarding location method's practical implementation. Despite the fact that multifrequency information is not provided, the lack of accuracy is partially overcome by the scenario division in cells (which reduce the search area) and the use of a calibration procedure based on RSS measurements taken at each cell. Preliminary results using the ZigBee nodes have been presented, highlighting the fact that it is possible to reach the initial accuracy requirement (error less than 5% of the indoor scenario's size).
This work has been supported by the "Ministerio de Ciencia e Innovaci n" of Spain/FEDER" under Projects TEC2008-01638/TEC (INVEMTA) and CONSOLIDER CSD2008-00068 (TERASENSE) and by the "Cátedra Telef nica- Universidad de Oviedo". The authors would like to thank Mr. Manuel Domínguez for his useful help in the measurements and software elaboration and Dr. Jaime Laviada and Dr. Javier Gutiérrez for manufacturing the monopole antenna.
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