Regional Sales Manager, Asia Pacific and ROW
Applanix Corporation 85 Leek Crescent Richmond Hill, Ontario CANADA
L4B3B3 (905) 709 4600
With the mobile mapping industry maturing and the number of applications and sensors onboard such vehicles growing, there is no doubt that moving from static to dynamic mapping has brought gains in productivity. However, with the growing number of systems being deployed worldwide there is no defined common standard for accuracy. Moreover, many systems in various stages of development or deployment are heavily customized, and suit the particular needs of individual clients rather than addressing the needs of various key stakeholders in key market verticals. Customization brings with it high system development costs and stifles mass adoption of mobile mapping technology. What is needed is a scalable solution which offers the highest accuracy possible and timely data which addresses the needs of various stakeholders and automates data collection. Automation and high accuracy are the salient elements which will satisfy the demands of mobile mapping data users at a price point which makes mass adoption possible. This paper introduces the Applanix LANDMark system, a fully supported commercial off the shelf and scalable mobile mapping solution which combines a high accuracy POS LV inertial GPS system with an automated asset acquisition system.
This paper addresses the key technologies and productivity gains of the Applanix LANDMark mobile mapping solution and how it can deliver both accuracy and automation to address the needs of users in various market verticals. Traditional methods of data acquisition (e.g. manual cataloging of assets, closing roadways to assess pavement condition) are more expensive than mobile mapping when considering the cost of labor and processing data. From the service provider's standpoint, the cost per asset or cost per road mile collected is constantly being driven lower. From the client's perspective whether it is a Department of Transportation requiring road asset data, urban planning requiring better street level data of neighborhoods or GIS data departments requiring more timely and accurate data to update databases, the needs of various organizations overlap and by collecting the highest accuracy data possible on a single pass makes the data product more ubiquitous. By serving the unique needs of all stakeholders, this makes the data
more affordable and valuable. In order to achieve high accuracy, the heart of the LANDMark system is the inertial GPS solution which is described in detail below.
POS LV DESCRIPTION
The POS LV system is a tightly coupled inertial/GPS system which is shown in Figure 1. Tightly-coupled implementation, optimally blends the inertial data with raw GPS observables from individual satellites (ranges and range rates). In this case if the number of visible satellites drops below four, the inertial navigator is still aided by the GPS. The result is improved navigational accuracy when compared to the free-inertial operation. An additional advantage of tightly-coupled integration is the improved reacquisition time to recover full RTK position accuracy after satellite signal loss (see ).
The inherent benefits of tightly-coupled data blending become readily apparent in the accuracy and integrity of the resulting navigation solution. By contrast, loosely-coupled implementation blends the inertial navigation data with the position and velocity output from the GPS. If the number of visible satellites is sufficient for the GPS to compute its position and velocity, i.e. four or more satellites, then GPS position and velocity are blended with the inertial data. Otherwise, if the GPS data is not available, the system will operate without any GPS aiding. The inertial navigator computes position, velocity and orientation of the IMU. The Kalman filter estimates the errors in the inertial navigator along with IMU, distance measurements instrument (DMI) and GPS receivers. System components are shown in Figure 2. With all POS LV system models there is the option of using OmniSTAR XP, HP or VBS corrections which eliminates the need for using a base station. Accuracies of 10, 20 and 30 to 50 centimeters in ideal conditions can be achieved with this system.
A standard feature on POS LV 220 and 420, the GPS Azimuth Measurement Subsystem (GAMS) integrates the IMU with a 2-antenna heading measurement system. As long as there is GPS coverage GAMS continuously calibrates the IMU and azimuth does not drift. A single-antenna configuration, in comparison, requires dynamic heading alignment and delivers heading measurements that suffer from drift. GAMS utilizes a carrier phase differential GPS algorithm to measure the relative position vector between the two antennas. The system uses carrier phase measurements from five or more satellites to estimate and, eventually, to identify a set of integer phase ambiguities for each satellite being tracked by both receivers. For the ambiguity resolution algorithm to work, both receivers must track at least five common satellites. Once tracking has been obtained, GAMS will continue to operate with as few as four satellites. The GAMS heading system will not provide measurements when fewer than 4 GPS satellites are available. During GPS outages, POS LV will continue to provide accurate heading measurements drifting at the rate of about 1 arc min/min. Accurate heading is critical for land based photogrammetric applications especially when intermittent or non existent GPS conditions occur over extended periods of time.
The distance measurement instrument (DMI) is another essential piece of the POS LV hardware which outputs pulses representing fractional revolutions of the instrumented wheel. These pulses are converted by the POS LV into measurements of incremental distance travelled by the vehicle when no GPS is available.
The Applanix LANDMark solution has been engineered to provide the best accuracy for multiple missions in several market verticals. The standard hardware and software for the system is comprised of a 1280×960 digital camera, computer, multiplexer and Applanix POS LV, GEOImage RT real time operating software, POSPac 5.0 Land IMU/GPS post processing and GEOImage Image processing and feature extraction software. This standard product bundle is utilized for asset image capture and database creation for DOTs requiring more accurate and timely data of as built infrastructure. An optional laser operating at 75 Hz mated with the standard product configuration can provide an accurate reflectivity signature. This reflectivity data is used for not only asset detection, but asset characterization and measurement as well. The LANDMark system is also able to be installed on rail vehicles to perform the same mission and record trackside assets and other features of interest.
Within the road maintenance segment, asset data capture needs to be coupled with road condition to maximize productivity on missions. With the simple addition of a camera aimed at the road, videolog data of the pavement service which is geo referenced can be captured as well. A full inventory of pavement data can be taken at highway speed which has the added benefit of not requiring costly lane closures. Within the GEOImage processing and feature extraction software, pavement distress can be classified and road fissures / cracking can actually be measured accurately. The user can set up a database with any criteria (distress type, length, width, location etc.). Once the data from a mission has been recorded, the GEOImage software can export the data in any format required.
The system hardware and software can address the needs of the power infrastructure management segment which requires an accurate inventory and status of all assets in the field. According to the GITA 2006 Geospatial Technology Report, asset management is reported as the second most important GIS application apart from trouble call/outage analysis (see ). This requires more automation in order to derive more accurate data for use in an enterprise environment. As illustrated in figure 3, when the LANDMark system is equipped with an optional 2048×2048 camera, details such as equipment ID numbers, condition of transformers and other relevant details can be recorded by the operator. The database information window which is shown as the sub window, can record any information of interest.
One of the more interesting applications to emerge in the last two years has been the merging of airborne and land based data sources for a host of situational awareness and mapping / visualization uses. Some of this data has already been utilized by millions of people in applications such as Google Street View and Microsoft Virtual Earth for generic
visualization. However, by utilizing a dodecahedron camera which can view through 11 CCDs at 32 frames per second and recording the precise position and orientation through the POS LV, users in the car navigation, law enforcement and emergency disaster response fields can now derive high resolution images in all fields of view from the location of the recording vehicle. More importantly, by using the Applanix GEOImage 360 software, users can accurately measure objects and features of interest within the entire field of view as illustrated by figure 4. The user has the capability to not only view the street level imagery, but look at an overhead view of the precise location of an area of interest. Depending on the mission, GEOImage 360 can record a number of different types of information and determine the precise geographical co-ordinate, height, length and width even in the most challenging GPS conditions. The LANDMark system performance can be tailored to the users' operating environment by accommodating any version of the POS LV.
LANDMark DATA ACQUISITION AND PROCESSING
The LANDMark mobile mapping solution hardware is designed to be modular to fit in any vehicle and suit the particular application. Within the electronics rack housing shown in figure 5, all versions of POS LV can be integrated along with the multiplexer, hard drives and onboard CPU which hosts the GEOImage data collection software. The CPU and multiplexer can accommodate future expansion of the system if the user wishes to change or add hardware. A key attribute of the system is its flexibility which can grow as the user requirements change without the need to re-invest in current hardware. For example, if a user wishes to employ automated feature extraction, the acquisition of a laser complete with the operating software and configurations files can be purchased at a later date. The same applies to the addition of cameras. Different missions require flexibility in camera resolution and this can be added and configured easily through the GEOImage RT (Real Time) operating software which offers a simple installation and calibration utility. In all up to 6 different devices can be supported with the standard equipment.
The LANDMark mobile mapping solution comprises a data acquisition and processing component. For real time data monitoring the operator utilizes the GEOImage RT viewer shown in figure 6 which provides essential data related to camera exposure, GPS condition, frame adjustment relative to vehicle velocity and hard drive usage. The intuitive GUI allows a single operator to view not only of the data being acquired but system status which offers
alerts to various anomalies and minimizes error on the first data pass virtually eliminating data re-acquisition. GEOImage RT controls all system hardware and synchronizes data from the POS LV, cameras and optional laser to ensure data accuracy for image processing. Depending on lighting conditions, vehicle velocity and type of data to be acquired, users can easily modify system settings to acquire imagery at fixed intervals (1 frame or 10 frames per second), or via the DMI if data needs to be acquired at fixed distances. Another critical piece of real time data monitoring software is the POSView controller which monitors the status of the POS LV system in real time. This serves as the setup and calibration utility which projects detailed information of GPS condition (DOP, SV etc), real time position estimation and various warning messages. The GUI can be customized as per the operator's preference.
During data acquisition the operator drives at highway speeds to record data of road surface and / or roadside assets. With most video based mobile mapping systems, stereo imaging is required to derive measurements within the imagery. With the LANDMark system however, multiple cameras are not required for asset management missions due to the system's ability to compare pixels from successive frames of time tagged imagery to derive very accurate measurements. With post processing of the POS LV system data with RTK, LANDMark consistently produces submeter level data even after prolonged absence of GPS. Utilizing a single camera for recording imagery saves the operator from having to purchase a second camera in order to produce stereo imagery and can utilize the other device for videolog data or utility survey.
LANDMark AUTOMATED DATA PROCESSING
As mentioned previously, one of the main requirements of mobile mapping systems is the ability to record and process timely information to be used by a multitude of stakeholder groups. However, with the increase in data acquisition capability comes the need for increased processing and up until now, most data processing has been a manual process. Operators must identify features of interest and populate databases manually. However, by utilizing laser reflectivity data the LANDMark system can perform automatic measurements and identification of objects such as street signs. During the mission, the video is time tagged with position and orientation from the POS LV, as well as the laser data. During post processing as illustrated in figure 7, the operator can scroll through the imagery manually and stop at a particular frame to zoom in on the area of interest. By highlighting the sign or attribute, the sub menu opens with the fields required to be populated with data (e.g. height, width, condition etc.). Once the operator has analyzed and populated the data fields, a sign recognition database can be accessed to look up sign codes to complete the analysis. With laser data recorded during the mission, the operator can allow the system to automatically conduct certain parts of the analysis. For example, by measuring the reflectivity of the sign, physical characteristics can be automatically derived such as shape and dimensions.
When post processing occurs with the laser data, the sub menu in figure 7 is automatically populated with the sign code, height and width information, along with the asset's position. The operator utilizing the laser information now only provides a quality check of the data instead of having to manually measure and enter the data. Using reflectivity data, the system can also characterize the asset itself by looking at measures of reflected light at the boarders of the sign as well as the characters on the sign itself. The databases which drive this automatic capability can be customized for use worldwide.
Utilizing this automatic asset recognition capability not only increases operator productivity, but maximizes database accuracy. During large data collects, it is not uncommon to have tens of thousands of assets needing measurement and condition assessment. To properly enter this information, on average it takes two minutes per asset. Putting this figure into perspective, a 10,000 asset data mission would require 400 personnel hours to process. With automatic feature extraction, the time involved in data processing can be cut by over 50% at a significant cost saving to the system operator.
This paper has described the LANDMark system and its key attributes as a modular and highly accurate mobile mapping system. In order to meet the increasing demands of users in very diverse segments, we have articulated how the system can be modified with various optional sensors to acquire and process data rapidly for road as well as rail applications. The suite of solutions available with the LANDMark system and its GEOImage software has demonstrated a level of flexibility which will be of interest to data users as well as mobile mapping vehicle operators.
- Scherzinger, B. Precise Robust Positioning with Inertial/GPS RTK Proceedings of IONGPS- 2000, Salt Lake City UH, September 20-23, 2000
- Geospatial Information & Technology Association 2006 Geospatial Technology Report, Aurora CO, 22, 2006.