Precision Of Location Estimates Research Articles

Multienvironment performance comparison of robot‐assisted indoor location estimation system

SummaryMany indoor location systems utilizing the fingerprinting technique require frequent signal map generation due to the dynamic properties of indoor environments. This time‐consuming task can be freed from human involvement by using various techniques. Thus, a robot‐aided signal map creator is implemented and its positioning performance as well as its mapping time is compared with a widely used human facilitated approach. For testing purposes, a low‐cost, low‐power, not off‐the‐shelf signal data collection robot is implemented. Its signal collection speed and location estimation precision is then compared with the manual method both in a small and large environment. The findings indicate that in the small environment, robot‐aided approach performs with 268‐cm error‐rate 70% of the time. On the other hand, the improved robot‐aided approach in large environment saves 52 min of labor‐intense legwork and achieves 303.5‐cm mean error‐rate.

Hybrid Fuzzy Centroid with MDV-Hop BAT Localization Algorithms in Wireless Sensor Networks

Many applications employing wireless sensor networks have been available in real-world scenarios. Their popularity is due to distinctive characteristics, for example, small scale, multisensing capability, and cost-effective deployment. However, there are constraints including routing, reliability, and especially localization, in particular without the aid of global positioning services, the lack of satellite coverage. In addition, if embedded, the overhead will be increased with hardware costs and shortened battery life. Thus, a range-free-based localization scheme is promising and is being pursued as a cost-effective approach. Centroid is one of the pioneer low complexity range-free estimation algorithms, and DV-Hop is another algorithm that has no requirements for distance information. However, their main drawbacks are location estimation precision. Recently, a soft-computing-based approach used to address uncertainty and approximation has been proposed as a low cost solution to gain precision, and, therefore, this research investigates its integration and then proposes a novel hybrid localization algorithm utilizing key characteristics of Centroid and DV-Hop. This hybrid scheme employs an extra weight with signal normalization derived from a fuzzy logic function in Centroid. The research also integrates a BAT algorithm of the modified DV-Hop. These combinations demonstrate the effectiveness in the simulation and location error reduction with time complexity trade-off.

The impact of CCD radiation damage on Gaia astrometry - I. Image location estimation in the presence of radiation damage

The Gaia mission has been designed to perform absolute astrometric measurements with unprecedented accuracy; the end-of-mission parallax standard error is required to be 30 micro-arcseconds for a G2V type star of magnitude 15. These requirements set a stringent constraint on the accuracy of the estimation of the location of the stellar image on the CCD for each observation: e.g., 0.3 milli-arseconds (mas) or 0.005 pixels for the same V=15 G2V star. However the Gaia CCDs will suffer from charge transfer inefficiency (CTI) caused by radiation damage that will degrade the stellar image quality and may degrade the astrometric performance of Gaia if not properly addressed. For the first time at this level of detail, the potential impact of radiation damage on the performance of Gaia is investigated. In this first paper we focus on the evaluation of the CTI impact on the image location accuracy. We show that CTI decreases the stellar image signal-to-noise ratio and irreversibly degrades the image location estimation precision. As a consequence the location estimation standard errors increase by up to 6% for a radiation damage level equivalent to the end-of-mission. In addition the CTI-induced image distortion introduces a systematic bias in the image location estimation (up to 0.05 pixels or 3 mas in the Gaia operating conditions). We present a novel approach to CTI mitigation that enables, without correction of the raw data, the unbiased estimation of the image location and flux from damaged observations. Its implementation reduces the maximum measured location bias for the faintest magnitude to 0.005 pixels (~4e-4 pixels at magnitude 15). In a second paper we will investigate how the CTI effects affect the final astrometric accuracy of Gaia by propagating residual errors through the astrometric solution.

Comparison of association mapping methods in a complex pedigreed population

Association mapping methods were compared using a simulation with a complex pedigree structure. The pedigree was simulated while keeping the present Danish Holstein population pedigree in view. A total of 15 quantitative trait loci (QTL) with varying effect sizes (10%, 5% and 2% of total genetic variance) were simulated. We compared the single-marker test, haplotype-based analysis, mixed model approach, and Bayesian analysis. The methods were compared for power, precision of location estimates, and type I error rates. Results found the best performance in a Bayesian method that included genetic background effects and simultaneously fitted all single-nucleotide polymorphisms (SNPs) with a variable selection method. A mixed model analysis that fitted genetic background effects and tested one SNP at a time performed nearly as well as the Bayesian method. For the Bayesian method, it proved necessary to collect SNP signals in intervals, to avoid the scattering of a QTL signal over multiple neighboring SNPs. Methods not accounting for genetic background (full pedigree information) performed worse, and methods using haplotypes were considerably worse with a high false-positive rate, probably due to the presence of low-frequency haplotypes. It was necessary to account for full relationships among individuals to avoid excess false discovery. Although the methods were tested on a cattle pedigree, the results are applicable to any population with a complex pedigree structure.

Locating the nodes: cooperative localization in wireless sensor networks

Accurate and low-cost sensor localization is a critical requirement for the deployment of wireless sensor networks in a wide variety of applications. In cooperative localization, sensors work together in a peer-to-peer manner to make measurements and then forms a map of the network. Various application requirements influence the design of sensor localization systems. In this article, the authors describe the measurement-based statistical models useful to describe time-of-arrival (TOA), angle-of-arrival (AOA), and received-signal-strength (RSS) measurements in wireless sensor networks. Wideband and ultra-wideband (UWB) measurements, and RF and acoustic media are also discussed. Using the models, the authors have shown the calculation of a Cramer-Rao bound (CRB) on the location estimation precision possible for a given set of measurements. The article briefly surveys a large and growing body of sensor localization algorithms. This article is intended to emphasize the basic statistical signal processing background necessary to understand the state-of-the-art and to make progress in the new and largely open areas of sensor network localization research.

Optimal seismic monitoring for event location with application to On Site Inspection of the Comprehensive Nuclear Test Ban Treaty

Seismic networks are used to monitor seismic activity including explosions and natural events such as earthquakes. Data from a seismic network are used to identify the occurrence of an event and to determine the source location. The precision of the location estimates is highly dependent on the network configuration. In this article we apply the statistical theory of optimal design to derive network configurations that maximize the precision of location estimates. We derive theoretical characterizations of optimal networks and bounds that can be used to benchmark networks when practical constraints are present. We also discuss practical issues that often arise in seismic monitoring. An application of particular importance for our results is On Site Inspection (OSI) of the Comprehensive Nuclear Test Ban Treaty. Suspected violations of the Treaty may lead the Treaty Organization to send an OSI team to investigate. One of the first tasks of the OSI team will be to deploy a mobile seismic network that can help pinpoint the source of the suspected blast from aftershock activity. Rapid deployment of an efficient network will be critical to the success of the mission. Our results provide a theoretical basis and practical guideline for configuring such a network.

Accuracy Tests for Sonic Telemetry Studies in an Estuarine Environment

We evaluated accuracy and precision of a directional sonic telemetry system and 2 positioning systems to study sea turtle (Cheloniidae) use of estuarine habitat in Core Sound, North Carolina. Accuracy and precision of location estimates affect the power of statistical tests for use of habitat studies and define the amount of movement that can be reliably measured. Angle errors associated with the sonic system averaged −2.5° ± 5.67 (SD) for a 95% error arc of ± 11.34° (range −17−12°). We obtained 45 location estimates after correcting 90 bearings for bias. Location errors (E), obtained from stationary positions at 400-1,200 m, ranged from 14.6 to 281.0 m with a median of 75.6 m. The 90 and 95% confidence areas for these data were 11.1 and 21.2 ha, respectively. Location error varied (P < 0.01) WITH GEOMETRIC MEAN DISTANCE (D g ) between receivers and transmitters. Areal measures of confidence obtained at the D g 500-600 m were the smallest (2.1-2.8 ha) among 3 distance intervals within 500-1,200 m. Attained levels of accuracy and precision were adequate to determine turtle movement and distribution in relation to selected fisheries activities, but of limited value for use of habitat studies. Inaccurate position estimates of monitoring platforms (e.g., boats) also affect location estimates. Precision of position estimates of a stationary boat anchored at a known location (i.e., channel marker) were poor, averaging 62 m, when obtained from Long Range Navigation System (LORAN). In contrast, positions obtained from Differential Global Positioning System (DGPS) varied by 3 m. The DGPS did not affect (P = 0.94) location estimation. Average difference between estimates using known location coordinates and those obtained from DGPS was 0.56 with a 95% confidence interval of ± 1.29 m. We recommend that DGPS be used when evaluating sea turtle use of habitat. The DGPS was more accurate than LORAN and was unaffected by geography