Geolocation Method Research Articles

小型机载光电平台中基于扩展卡尔曼滤波的地面目标定位算法

小型机载光电平台中基于扩展卡尔曼滤波的地面目标定位算法

Vision-Based Target Three-Dimensional Geolocation Using Unmanned Aerial Vehicles

This paper develops a method of calculating the three-dimensional (3-D) coordinates of a target with image information taken from an unmanned aerial vehicle (UAV). Unlike the usual approaches to target geolocation that rely heavily on georeferenced terrain database or accurate attitude sensors, the contribution of the proposed method is to offset the constraints and also perform 3-D geolocation of the target based on the relative altitude between the aircraft and the target calculated using the stereo vision technique. Considering the poor performance of the yaw-angle measurement provided by the low-quality attitude sensors in the UAV, a novel vision-based 3-D geolocation method is designed. The proposed method is proven to be valid and practical via simulation results and actual flight experiments.

IP Geolocation based on identification routers and local delay distribution similarity

SummaryIP geolocation is usually used in fog computing to avoid high latency and discriminate malicious requests by judging the location of users. Existing delay measurement‐based IP geolocation approaches are not applicable to the network that has hierarchical topology and weak connectivity, and the precision of the classical Street‐Level Geolocation (SLG) method will decrease dramatically when the common routers are anonymous. In this paper, an IP geolocation method based on identification routers and local delay distribution similarity is proposed. The target IP's location at city‐level is firstly derived by matching its routing path with the identification routers that only forward packets to the same city. After that, the target IP's local delay between the nearest common router and the target IP is gathered, and the landmarks' are obtained at the same time. Finally, the location of the landmark that has the most similar local delay distribution with the target IP is taken as the geolocation result. Theoretical analysis and experimental results show that the proposed method can derive reliably geolocation results at city‐level for the target IP in the network with hierarchical architecture. Moreover, the geolocation accuracy of classical SLG method is improved obviously when the common routers are anonymous.

AOA Measurement based Localization Using RLS Algorithm under NLOS Environment

In localization problem, the estimation accuracy of a target location is one of the most significant issues. The global positioning system (GPS) that is the most widely used localization method can be disrupted by some disturbances under non-line-of-sight (NLOS) condition such as indoor environment and downtown. In this paper, we suggest a localization algorithm using the angle of arrival (AOA) measurements. AOA measurement based localization is one of the most efficient geolocation methods that use a wireless active signal. Moreover, AOA method has an advantage that only two base stations are required to estimate the target location. In all kinds of localization methods using wireless signal, the NLOS and measurement noise are the significant problems that decrease an estimation accuracy of a target location. In this paper, we suggest a Kalman filter based hypothesis test and a recursive least square scheme to overcome NLOS and measurement noise problem, respectively. Using Kalman filter based hypothesis test, the measurement data set from each base station can be identified whether it contains the NLOS noise or not. Also, recursive least square (RLS) scheme can obtain the precise location of a target with rapid calculation speed when additional measurement data is received from auxiliary base stations. Simulation result confirms the high estimation accuracy and computational speed of our proposed scheme.

A summary of oil and gas exploration in the Great Australian Bight with particular reference to southern bluefin tuna

Abstract Large numbers of juvenile southern bluefin tuna (SBT; Thunnus maccoyii) migrate into the warm shelf waters of the Great Australian Bight (GAB) each austral summer. Whilst in the GAB, they are the focus of a commercially important Australian fishery. Recent expansion of activities associated with oil and gas exploration in the GAB over the last five years has raised concerns that noise associated with geophysical surveys and exploratory drilling activities may impact on the migration and behaviour of SBT, with potential flow-on effects on the commercial fishery and current monitoring of the population for management purposes. As a first step in identifying the potential impacts of expansion of oil and gas exploration activities in the GAB on SBT, we establish the historical extent of these activities in the GAB with a primary focus on geophysical surveys. Potential overlap with the distribution of juvenile SBT in the GAB determined from an archival tag dataset (1998–2011) was then explored. Geophysical surveys have occurred throughout the vast majority of the region since 1960, with the size of energy sources used in surveys and the extent of areas surveyed increasing through time. The use of more complex, higher density 3D surveys has increased gradually since 2000. The timing and distribution of exploration activity has had varying degrees of overlap with SBT occurrence and distribution as described by tagged fish. Determining robust measures of the responses to surveys however, is difficult due to a paucity of data on the hearing capabilities of SBT, uncertainties in the true extent of spatial overlap of activities and tagged fish resulting from geolocation methods used for position estimation from archival tag data, complexities in the drivers of behaviour in SBT, and limitations with using observational data to determine cause-and-effect relationships. These difficulties are typical not just of SBT and the GAB region, but apply to investigations of the responses of marine animals to geophysical surveys more broadly. The data presented in this study, however, represent a first step towards understanding oil and gas exploration within a defined region of the Australian marine environment, and provide important context for exploring the potential impact of such activities on a commercially important top order predator of the GAB ecosystem.

AN IMPROVED METHOD OF AGM FOR HIGH PRECISION GEOLOCATION OF SAR IMAGES

Abstract. In order to take full advantage of SAR images, it is necessary to obtain the high precision location of the image. During the geometric correction process of images, to ensure the accuracy of image geometric correction and extract the effective mapping information from the images, precise image geolocation is important. This paper presents an improved analytical geolocation method (IAGM) that determine the high precision geolocation of each pixel in a digital SAR image. This method is based on analytical geolocation method (AGM) proposed by X. K. Yuan aiming at realizing the solution of RD model. Tests will be conducted using RADARSAT-2 SAR image. Comparing the predicted feature geolocation with the position as determined by high precision orthophoto, results indicate an accuracy of 50m is attainable with this method. Error sources will be analyzed and some recommendations about improving image location accuracy in future spaceborne SAR's will be given.

Crowd-sourced pictures geo-localization method based on street view images and 3D reconstruction

Abstract People are increasingly becoming accustomed to taking photos of everyday life in modern cities and uploading them on major photo-sharing social media sites. These sites contain numerous pictures, but some have incomplete or blurred location information. The geo-localization of crowd-sourced pictures enriches the information contained therein, and is applicable to activities such as urban construction, urban landscape analysis, and crime tracking. However, geo-localization faces huge technical challenges. This paper proposes a method for large-scale geo-localization of crowd-sourced pictures. Our approach uses structured, organized Street View images as a reference dataset and employs a three-step strategy of coarse geo-localization by image retrieval, selecting reliable matches by image registration, and fine geo-localization by 3D reconstruction to attach geographic tags to pictures from unidentified sources. In study area, 3D reconstruction based on close-range photogrammetry is used to restore the 3D geographical information of the crowd-sourced pictures, resulting in the proposed method improving the median error from 256.7 m to 69.0 m, and the percentage of the geo-localized query pictures under a 50 m error from 17.2% to 43.2% compared with the previous method. Another discovery using the proposed method is that, in respect of the causes of reconstruction error, closer distances from the cameras to the main objects in query pictures tend to produce lower errors and the component of error parallel to the road makes a more significant contribution to the Total Error. The proposed method is not limited to small areas, and could be expanded to cities and larger areas owing to its flexible parameters.

Geolocating a WeChat user based on the relation between reported and actual distance

The combination of social networks and the Internet of Things has raised a new wave of network technology application. However, the presence of malicious social network users poses a potential threat to Internet of Things security, and the research on social network user geolocation technology is of great significance. The accuracy of existing geolocation methods for WeChat users depends on the stable correspondence between the reported distance and actual distance. In view of the difficulty to pinpoint users’ location in the real world due to WeChat location protection strategy, a WeChat user geolocation algorithm based on the reported and actual distance relation analysis is proposed. The proposed algorithm selects the target reported distance and determines the initial target space based on statistical characteristics of the relation between the reported distance and actual distance. What is more, stepwise strategies are taken to improve the accuracy rate of space partition. Experimental results show that, on the premise that target users can be discovered, the proposed algorithm could achieve higher accuracy compared with the classical space partition–based algorithm and the heuristic number theory based algorithm. The highest geolocation accuracy is within 10 m and 56% of geolocation results are within 60 m.

Twitter user geolocation by filtering of highly mentioned users

Geolocated social media data provide a powerful source of information about places and regional human behavior. Because only a small amount of social media data have been geolocation‐annotated, inference techniques play a substantial role to increase the volume of annotated data. Conventional research in this area has been based on the text content of posts from a given user or the social network of the user, with some recent crossovers between the text‐ and network‐based approaches. This paper proposes a novel approach to categorize highly‐mentioned users (celebrities) into Local and Global types, and consequently use Local celebrities as location indicators. A label propagation algorithm is then used over the refined social network for geolocation inference. Finally, we propose a hybrid approach by merging a text‐based method as a back‐off strategy into our network‐based approach. Empirical experiments over three standard Twitter benchmark data sets demonstrate that our approach outperforms state‐of‐the‐art user geolocation methods.

Extending the Stansfield Algorithm to Three Dimensions: Algorithms and Implementations

The Stansfield algorithm is a well-known geolocation method for two-dimensional (2-D), azimuth-only bearing measurements of a stationary emitter. It is known to suffer from estimation bias, and its performance in terms of optimality criteria is unknown. Strategies that accurately combine both azimuth and elevation measurements for 3-D position estimation are generally required in many applications. This paper introduces two novel bearings-only geolocation algorithms: the weighted Stansfield algorithm in three dimensions (WS3D) and the instrumental variable weighted Stansfield algorithm in three dimensions (IVWS3D). In these two procedures, bearing quality weighting and estimated range weighting are used to minimize the maximum-likelihood cost function in pairs of coupled least-squares procedures. Measurement weighting is shown to be important to obtain best performance. Moreover, the use of updated bearing measurements in the instrumental variable method in IVWS3D is shown to decrease estimation bias. Simulations of the new algorithms show that the WS3D algorithm asymptotically outperforms existing geolocation algorithms, whereas the IVWS3D algorithm provides the least-biased position estimation.

一种基于POS系统的航空相机目标定位方法

一种基于POS系统的航空相机目标定位方法

Twilight‐free geolocation from noisy light data

Abstract Solar geolocation is used to quantify the movements of animals tagged with sensors that record ambient light with respect to time. Global location sensor (GLS) tags are small, light, and present minimal drag or wing loading. They are affordable, and some can record data for several migratory cycles. These benefits mean they can be used in applications for which satellite tags are unsuitable. However, large errors in estimated locations can result if the sensor is obscured, especially around twilight, and sometimes the data obtained is unusable by existing methods of analysis due to this source of noise. This places limitations on the usefulness of solar geolocation in conservation and monitoring efforts. All existing methods of analysis are dependent on twilights being identifiable or faithfully recorded. Instead, the method introduced here depends on the overall pattern of day and night to calculate the likelihoods for a Hidden Markov Model, where the hidden states are geographic locations. We call this a “twilight‐free” method of light‐based geolocation. This method quickly estimates locations from otherwise unusable noisy light data. We use examples to show that the method produces tracks that are comparable in accuracy and precision to other geolocation methods. Furthermore, efficiency and replicability of estimated paths are improved because the user does not have to subjectively identify twilights. Other data sources, such as sea surface temperature and land or sea masks are easily incorporated, further improving location estimates and processing speed. The twilight‐free method offers new opportunities to researchers interested in the movements of animals that routinely have obscured sensors, or to analyse previously unusable noisy light data. It offers a fast, efficient, and replicable method for analysing tag data without the need for time‐consuming pre‐ or post‐processing. By increasing the yield of usable data from GLS tagging studies, researchers can more efficiently quantify where animals are going and when, and monitor changes in habitat. This is of fundamental importance to management and conservation efforts.

GeoPose3K: Mountain landscape dataset for camera pose estimation in outdoor environments

Abstract We introduce a new dataset called GeoPose3K 1 which contains over three thousand precise camera poses of mountain landscape images. In addition to camera location and orientation, we provide data for the training and evaluation of computer vision methods and applications in the context of outdoor scenes; synthetic depth maps, normal maps, illumination simulation and semantic labels. In order to illustrate properties of the dataset, we compare results achieved by state-of-the-art visual geo-localization method on GeoPose3K with results achieved on an existing dataset for visual geo-localization. So as to foster research of computer vision algorithms for outdoor environments, several novel future use-cases of our new GeoPose3K dataset are proposed.

Motion-Extended Array Synthesis—Part I: Theory and Method

We consider the realization of motion-extended array synthesis (MXAS), in the RF and acoustic sensing domains, for the purpose of achieving high resolution in imaging, direction finding (DF), and geolocation applications. The focus is on a method in which, like synthetic aperture radar (SAR), the aperture synthesized is much larger than any aspect of the physical system, but, unlike SAR, in which there is no reference waveform available to exploit. We show that arbitrarily large virtual arrays, limited only by antenna element field of view, can be created by moving one collection system away from another, sweeping out a 1-D or 2-D area. The virtual array so created is suitable for use in general signal environments, including complex scenarios with cochannel and/or ultraweak sources. In the MXAS processing construct, the temporally distributed array formation is cast into a form resembling standard array processing and affording the same degrees of freedom as a real array of the same size. A performance assessment comparing an MXAS implementation to a leading method for DF and geolocation shows orders of magnitude improvement for MXAS, and conformance to the Cramer–Rao lower bound for DF for an array, under the correct interpretation of motion extension. Finally, we discuss candidate application areas.

The importance of elevation angle measurements in HF radar investigations of the ionosphere

AbstractWe evaluate the performance of three methods for determining the ground range and refractive index of ionospheric scattering volumes. Each method uses the same equivalent path analysis with the latter parameter derived through the additional use of Snell's law. Two of these methods make their predictions using the group range and a virtual height model for each scattering volume; the third method uses the group range and the elevation angle of the ray. The effectiveness of each of these methods is evaluated using ray tracing through a simulated reference ionosphere. Ray tracings provide determinations of the initial elevation angle and group range of the transmitted signal and the ground range and refractive index of the scattering volume. The first pair of parameters is used as inputs to the geolocation methods, and the second pair becomes part of a data set against which the predictions of the geolocation methods are evaluated. We find that the geolocation methods using virtual height models change the initial elevation angle to a value that is consistent with their virtual height model but inconsistent with ray tracing. Consequently, predictions of ground range and refractive index from methods using virtual height models are rarely consistent with predictions from ray tracing. In contrast, the third method uses the initial elevation angle from ray tracing and yields accurate predictions in the bottomside ionosphere. Two modifications were made to this method to extend the agreement between it and ray tracing to all backscattered signals.

Smartphone-based geolocation of Internet hosts

The location of Internet hosts is frequently used in distributed applications and networking services. Examples include customized advertising, distribution of content, and position-based security. Unfortunately the relationship between an IP address and its position is in general very weak. This motivates the study of measurement-based IP geolocation techniques, where the position of the target host is actively estimated using the delays between a number of landmarks and the target itself. This paper discusses an IP geolocation method based on crowdsourcing where the smartphones of users operate as landmarks. Since smartphones rely on wireless connections, a specific delay-distance model was derived to capture the characteristics of this novel operating scenario.

Direct TDOA geolocation of multiple frequency‐hopping emitters in flat fading channels

The classic two-step approach for time difference of arrival (TDOA) geolocation is suboptimal since the TDOA measurements have not followed the constraint that all measurements should be consistent for a geolocation of a single emitter. In this study, the direct TDOA geolocation approach is proposed for frequency-hopping (FH) emitters. It makes use of the sparsity of the FH signals in frequency domain, and constructs a cross correlation function (CCF) matrix in frequency domain, then the location estimate is obtained by searching the maximum eigenvalue of the CCF matrix in a two dimensional grid. The Cramer–Rao lower bound has been derived. The resolution for a single FH signal geolocation is also analysed. Further, an extension of the new method for multiple FH emitters direct TDOA geolocation has been presented. The performance comparison between the direct approach and the conventional two-step method has been made by simulations. The results demonstrated that the proposed method outperforms the conventional two-step method. The simulations also demonstrated the effectiveness of the new method in locating multiple FH emitters.

A Principal Component Analysis of Vertical Temperature Profiles for Tracking Movements of Large Pelagic Fishes

Pop-up satellite archival tag (PSAT) technology that records depth, temperature, and light-level data has expanded the understanding of free-swimming behavior for numerous pelagic animals. Astronomical algorithms using these light-level data have allowed geolocation estimates of daily longitude and latitude. However, many pelagic animals have a crepuscular behavior pattern in which individuals are at depths below the photic layer during the day, thus precluding the use of traditional light-based movement algorithms for geolocation in such species as swordfish. A principal component analysis (PCA) of temperature profiles is described herein that utilizes depth and temperature data rather than light to estimate the horizontal movement between the initial location of tag release and transmission. PSAT data from swordfish (n=4), blue marlin (n=14), white marlin (n=2), and black marlin (n=1) were used to generate daily coordinate estimates. The marlin data provided sufficient light information to derive geolocation estimates using two light-based state space models, while the hydrographic PCA model was used to derive comparison estimates. Comparisons of the two model types show an average root mean square difference of 175.4 km demonstrating that the PCA model can be used to extract the movement of tagged swordfish and other pelagic species demonstrating crepuscular behavior. Integration of this PCA-based geolocation methods with both the best available estimates of the ocean temperature at the time of tag deployment and the existing light-based geolocation models would provide additional information on fine-scale movement of tagged fish.

Signals of opportunity geolocation methods for urban and indoor environments

Motivated by the geolocation requirements of future mobile network applications such as portable internet of things (IoT) devices and automated airborne drone systems, this paper aims to provide techniques for improving device geolocation estimates in urban and indoor locations. In these applications low size, weight and power are vital design constraints. This paper proposes methods for improving the geolocation estimate available to a system in indoor and urban environments without the need for addition sensing or transmitting hardware. This paper proposes novel system application techniques that enable the integration of signals of opportunity, providing a robust geolocation estimate without any additional hardware. The proposed method utilises a sinusoidal Kalman filter architecture to analyse raw radio frequency (RF) signals that surround a system in urban and indoor environments. The introduced techniques efficiently analyse the raw RF data from any signal of opportunity and combine it with higher level geolocation sensors to provide an improved geolocation estimate. The improvements achieved by the system in a range of environments have been simulated, analysed and compared to the results obtained using the prior art. These improvements have been further validated and benchmarked by hardware test. The results obtained provide evidence that the efficient use of signals of opportunity coupled with common navigation sensors can provide a robust and reliable geolocation system in indoor and urban environments.

Error analysis of ephemeris calibration for dual-satellite TDOA/FDOA geolocation

In this paper, we provide a theoretical error analysis of a satellite ephemeris calibration for the dual-satellite TDOA/FDOA geolocation method. First, the error covariance matrix for the ephemeris calibration is derived. Then, the result is incorporated into the error covariance matrix for geolocation. The derived equation is numerically evaluated to provide an intensive error analysis in time and spatial coordinates. Further, Monte Carlo simulation results are provided, and it is shown that the theoretical results coincide with the Monte Carlo simulation results.