Open Geospatial Consortium

Open Geospatial Consortium
Submission Date: 2018-03-20
Approval Date: 2018-08-27
Publication Date: 2018-12-19
External identifier of this OGC® document: http://www.opengis.net/doc/BP/cdb-core-primer/1.1
Version 1.1
Internal reference number of this OGC® document: 15-120r5
Category: OGC® Best Practice
Editor: Carl Reed

Volume 0: Primer for the OGC CDB Standard:
Model and Physical Data Store Structure
Copyright notice
Copyright © 2018 Open Geospatial Consortium
To obtain additional rights of use, visit http://www.opengeospatial.org/legal/.

Warning
This document defines an OGC Best Practices on a particular technology or approach
related to an OGC standard. This document is not an OGC Standard and may not bereferred to as an OGC Standard. It is subject to change without notice. However, thisdocument is an official position of the OGC membership on this particular technology
topic.

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OGC® Best PracticeApproved
English1
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Contents
1.

What is a CDB Conformant Data Store? .................................................................... 82.

Conformance ............................................................................................................. 10

3.

Normative and Informative References .................................................................... 10

4.

Terms and Definitions............................................................................................... 10
4.1

Abbreviations ..................................................................................................... 11

5.

Using OGC standards with a CDB structured data store .......................................... 11

6.

Background and informative material ...................................................................... 13
6.1

Intended Audience.............................................................................................. 13

6.2

Problem Definition ............................................................................................. 13

6.3 Use of a CDB conformant data store as an Off-line Data store Repository....... 15
6.4 Use of a CDB conformant data store as a Combined Off-line and Run-time Data
store Repository ............................................................................................................ 15
6.5

Client-Device Independence .............................................................................. 15

6.6

Runtime Publisher .............................................................................................. 15

6.7

Synthetic Environment Scalability & Adaptability............................................ 16

6.8

Simulator Wide Unique Data Representation .................................................... 20

6.9

Key Benefits of the CDB Standard .................................................................... 21

6.9.1

Improved Synthetic environment Data Store(DB) Generation Timeline ... 21

6.9.2

Interoperable Simulation-Ready Synthetic environment Data Store .......... 22

6.9.3

Improved Client-device Robustness/Determinism ..................................... 22

6.9.4

Runtime-Adjustable Synthetic Environment DB Correlation and Fidelity 22

6.9.5

Increased Synthetic Environment Data Store Longevity ............................ 23

6.9.6

Reduced Synthetic Environment Data Store Storage Infrastructure Cost .. 23

6.10

CDB Model Overview .................................................................................... 24

6.10.1

CDB Standard Data Representation and Organization ............................... 24

6.10.2

CDB Standard Logical Structure ................................................................ 25

6.10.3

Tile/Layer/Level-of-Detail Structure .......................................................... 26

6.10.4

CDB Structure, Organization on Media and Conventions.......................... 28

6.10.5Use of CDB in Applications Requiring Dynamic Synthetic Environments 29

6.10.6

Synthetic Environment Data Store Correlation .......................................... 30

Annex A: Revision history................................................................................................ 31
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Annex B: References ........................................................................................................ 32

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Abstract

The CDB standard defines a standardized model and structure for a single, “versionable,”
virtual representation of the earth. A CDB structured data store provides for a geospatial
content and model definition repository that is plug-and-play interoperable between
database authoring workstations. Moreover, a CDB structured data store can be used as acommon online (or runtime) repository from which various simulator client-devices cansimultaneously retrieve and modify, in real-time, relevant information to perform theirrespective runtime simulation tasks. In this case, a CDB is plug-and-play interoperable
between CDB-compliant simulators. A CDB can be readily used by existing simulationclient-devices (legacy Image Generators, Radar simulator, Computer Generated Forces,etc.) through a data publishing process that is performed on-demand in real-time.
The application of CDB to future simulation architectures will significantly reduceruntime-source level and algorithmic correlation errors, while reducing development,
update and configuration management timelines. With the addition of the High Level
Architecture - -Federation Object Model (HLA/FOM)1 and DIS protocols, the applicationof the CDB standard provides a Common Environment to which inter-connected
simulators share a common view of the simulated environment.
The CDB standard defines an open format for the storage, access and modification of asynthetic environment database. A synthetic environment is a computer simulation that
represents activities at a high level of realism, from simulation of theaters of war tofactories and manufacturing processes. These environments may be created within asingle computer or a vast distributed network connected by local and wide area networks
and augmented by super-realistic special effects and accurate behavioral models. SE
allows visualization of and immersion into the environment being simulated2.
This standard defines the organization and storage structure of a worldwide synthetic
representation of the earth as well as the conventions necessary to support all of thesubsystems of a full-mission simulator. The standard makes use of several commercial
and simulation data formats endorsed by leaders of the database tools industry. A seriesof associated OGC Best Practice documents define rules and guidelines for data
representation of real world features.
The CDB synthetic environment is a representation of the natural environment including
external features such as man-made structures and systems. A CDB data store can
include terrain relief, terrain imagery, three-dimensional (3D) models of natural and manmade cultural features, 3D models of dynamic vehicles, the ocean surface, and the ocean
bottom, including features (both natural and man-made) on the ocean floor. In addition,
the data store can includes the specific attributes of the synthetic environment data as
well as their relationships.
The associated CDB Standard Best Practice documents provide a description of a data
schema for Synthetic Environmental information (i.e. it merely describes data) for use in1

https://en.wikipedia.org/wiki/High-level_architecture

2 "Department of Defense Modeling and Simulation (M&S) Glossary", DoD 5000.59-M,

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simulation. The CDB Standard provides a rigorous definition of the semantic meaningfor each dataset, each attribute and establishes the structure/organization of that data as aschema comprised of a folder hierarchy and files with internal (industry-standard)
formats.
A CDB conformant data store contains datasets organized in layers, tiles and levels-ofdetail. Together, these datasets represent the features of a synthetic environment for the
purposes of distributed simulation applications. The organization of the synthetic
environmental data in a CDB compliant data store is specifically tailored for real-time
applications.
ii.
Keywords
The following are keywords to be used by search engines and document catalogues.
ogcdoc, OGC document, CDB, Common Data Base, simulation, synthetic environment,
virtual, primer, data storeiii.

Preface and Patent Call

The initial CDB specification was developed under a competitive contract awarded to
CAE to meet requirements of the United States Special Operations Command.
The CDB standard is widely implemented by multiple, independent industry contractors
for end-user simulation and mission rehearsal customers in many different countries overa period of ten years.
The industry-maintained CDB model and data store structure has been discussed anddemonstrated at OGC Technical Committee meetings beginning in September, 2013.
At the suggestion of several attendees at the first CDB ad-hoc meeting in September,
2014, the current version of the existing CDB standard was slightly reformatted forconsideration as an OGC Best Practice. The OGC Best Practice is the basis of work forthis OGC standard.
Attention is drawn to the possibility that some of the elements of this document may be
the subject of patent rights. The Open Geospatial Consortium shall not be held
responsible for identifying any or all such patent rights.
Recipients of this document are requested to submit, with their comments, notification of
any relevant patent claims or other intellectual property rights of which they may beaware that might be infringed by any implementation of the standard set forth in thisdocument, and to provide supporting documentation.

Submitting organizationsiv.
The following organizations submitted this Document to the Open Geospatial
Consortium (OGC):
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CAE Inc.
Carl Reed, OGC Individual Member
Envitia, Ltd
Glen Johnson, OGC Individual Member
KaDSci, LLC
Laval University
Open Site Plan
University of Calgary
UK Met Office
The OGC CDB standard is based on and derived from an industry developed andmaintained specification, which has been approved and published as OGC Document 15003: OGC Common Data Base Volume 1 Main Body. An extensive listing ofcontributors to the legacy industry-led CDB specification is at Chapter 11, pp 475-476 inthat OGC Best Practices Document(https://portal.opengeospatial.org/files/?artifact_id=61935).
v.

Submitters

All questions regarding this submission should be directed to the editor or thesubmitters:
Name

Affiliation

Carl Reed

Carl Reed & Associates

David Graham

CAE Inc.

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1.

What is a CDB Conformant Data Store?

A CDB3 conformant data store provides a representation of the whole earth optimized forvery high speed access and visualization. The physical data store model divides the earth
geographically into geodetic tiles. Each tile is defined by a latitude/longitude boundary.
Each tile contains one or more specific sets of features. The CDB model uses the WGS84 coordinate reference system (CRS). Details of the model along with implementation
requirements are provided in Volume 1: OGC CDB Core [16-113r3]. Any simulator
client-devices access CDB geospatial content using a WGS-84 CRS based indexing andtiling scheme. The physical and logical tiling system specified in the CDB standard issimilar to an equal area implementation of a Discrete Global Grid System (DGGS)4.
However, the implementation predates the OGC DGGS standards work and as such does
not implement all the OGC DGGS requirements.
A CDB data store contains the features and modeled representation of the synthetic
environment. A CDB data store can contain:
●
●
●
●
●
●

terrain altimetry,
planimetry,raster imagery,
attribution,
3D features with their modeled geometry,texture and attribution.

This standard also makes provision for the representation of moving models. An example
of a moving model is a tank moving across the terrain as viewed by a helicopter pilot.
The representation of moving models is comprehensive and goes well beyond othervisualization standards because it makes provisions for the standardized naming
conventions, material and feature attribution, radar/laser reflectivity, aircraft and airport
lighting systems, armaments, special effects, collision points/volumes just to name a few.
These provisions ensure interoperable simulation applications that are accessing a CDB
structured data store.
The CDB standard governs all requirements of the CDB data store, as follows:••

Data content and representation of the synthetic environment;
Structure and organization of the synthetic environment; and3Formerly known as Common Database the OGC Members determined that going forward that thisstandard shall be known as “CDB”.
4
Please go to http://www.opengeospatial.org/projects/groups/dggsswg for information on an OGC
candidate DGGS standard.

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File format of the synthetic environment as stored on media.

The CDB standard describes a modeled environment representation for distributed
simulation applications. Section 6.10.5 of this document, “Use of CDB in Applications
Requiring Dynamic Synthetic Environments”, discusses how a CDB-compliant simulator
could be adapted to handle modifications of the synthetic environment in real-time.
Given that a CDB data store defines a structured storage structure for representation andattribution of terrain, geographic objects, moving objects and entities, it is possible todesign a broad range of synthetic environment simulations that modify synthetic
environments in real-time. Such simulations can modify the CDB data store and thennotify other systems in a simulation federate5 that share a CDB data store about thechanges. This provides a synthetic environment (SE) that is persistent and fully correlated
across all simulation federates. For example, terrain “trafficability” could be handled bya new SE simulation that dynamically calculates soil moisture content as a function of
localized rain precipitation and soil types/composition. A second simulation would thenderive the resulting soil physics and determine vehicle wheel slippage across the varying
terrain conditions.
The modification/notification approach is well-suited for a broad gamut of simulations.
However, some simulations are very data intensive and require excessive broadcasting
bandwidths to other federates. In such cases, these dynamic simulations would have tobe replicated in the other client-devices of the federation. Good examples of this arevisual system special effects (e.g., rotor downwash effect, missile plumes, muzzle
flashes, cast landing lights). Typically such simulations are proprietary and intrinsic tothe client-devices. Other examples of this include the varying effects of weather6 (local
winds, temperature, humidity, particulates, etc.) and oceans (currents, temperature, etc.).
For ease of editing and review, the standard has been separated into 12 Volumes and aschema repository.
● Volume 0: OGC CDB Companion Primer for the CDB standard. (Best Practice)● Volume 1: OGC CDB Core Standard: Model and Physical Data Store Structure.
The main body (core) of the CBD standard (Normative).
• Volume 2: OGC CDB Core Model and Physical Structure Annexes (BestPractice).
● Volume 3: OGC CDB Terms and Definitions (Normative).
● Volume 4: OGC CDB Use of Shapefiles for Vector Data Storage (Best Practice).
5 This usage of federate and federation comes from IEEE Std 1516 in the context of Federation Object

Models (FOM) and Simulation Object Models (SOM). Common HLA terminology: Federate - an HLA
compliant simulation entity. Federation - multiple simulation entities connected via the RTI using acommon OMT.
6
Time-varying weather simulation effects could be simulated by a “weather server” simulation
subsystem which in turn can rely on the terrain elevation and terrain material datasets to perform its
simulation of weather in real-time.

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●
●
●
●
●

Volume 5: OGC CDB Radar Cross Section (RCS) Models (Best Practice).
Volume 6: OGC CDB Rules for Encoding Data using OpenFlight (Best Practice).
Volume 7: OGC CDB Data Model Guidance (Best Practice).
Volume 8: OGC CDB Spatial Reference System Guidance (Best Practice).
Volume 9: OGC CDB Schema Package: provides the normative schemas for key
features types required in the synthetic modelling environment. Essentially, theseschemas are designed to enable semantic interoperability within the simulation
context. (Normative)● Volume 10: OGC CDB Implementation Guidance (Best Practice).
● Volume 11: OGC CDB Core Standard Conceptual Model (Normative)● Volume 12: OGC CDB Navaids Attribution and Navaids Attribution
Enumeration Values (Best Practice)2.

Conformance

Not applicable for this Best Practice document.

3.

Normative and Informative References

The following are the key normative references for this Primer
Volume 1: OGC CDB Core Standard: Model and Physical Data Store Structure.
Volume 11: OGC CDB Core Standard Conceptual Model
The following informative references are applicable for this Primer.
HLA [IEEE Std 1516]: 1516-2010 - IEEE Standard for Modeling and Simulation (M&S)
High Level Architecture (HLA) - Framework and Rules
DIS [IEEE Std 1278]: 1278.1-2012 - IEEE Standard for Distributed Interactive
Simulation--Application Protocols

4.

Terms and Definitions

A complete glossary of Terms and Definitions used in this standard are contained in OGC
CDB Volume 3. The following description of a synthetic environment is provided ascontext for this Primer.
The synthetic environment is a representation of the natural environment at a specificgeographical location including the external features of the man-made structures andsystems. Therefore, the synthetic environment includes the terrain, the terrain features(both natural and manmade), three-dimensional (3D) models of vehicles, the ocean
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surface, and the ocean bottom, including features (both natural and man-made) on theocean floor. In addition, the synthetic environment includes the specific attributes of thesynthetic environment data as well as their relationships. The CDB Standard is morethan just a means of creating visual (aka out-the-window) scenery. Unlike othersimulation industry standards that only deal with data representational types of polygons,
colors, and textures, CDB deals with all the data types needed in high-end virtual andconstructive simulation applications.
4.1
Abbreviations
CGF Computer Generated Forced
DB
Database
DIS Distributed Interactive Simulation [IEEE std 1278]
DBGF Database Generation Facility [IEEE std 1516]
IG
Image Generator
LOS Line of Sight
NVG Night Vision Googles
OTW Out the Window
RTP Runtime Publisher

5.

Using OGC standards with a CDB structured data store7

The U.S. Department of Defense (DoD) developed the Joint Training Data Services(JTDS) to support rapid scenario generation for the U.S. DoD M&S training community.
The recently developed (2014) and deployed JTDS Common Terrain Generation Service(C-TGS) is a cloud-based service for the war fighter. C-TGS provides a robust capability
to search, discover and retrieve Modeling and Simulation (M&S) terrain data. JTDS
based the CB-TGS standard data structure on OGC-approved formats served by OGC
Web Services. The goal for the Terrain Generation Service (TGS): Eliminate the current
paradigm where every simulation uses a different proprietary format. Current data efforts
are fraught with simulation issues and errors, and data mining, correlation and processing
to support multiple simulation formats is manpower intensive.
The TGS Solution: Have a repository and user interface that provides access to a single
source of data through a persistent web service AND set and enforce a standard data
structure based on industry standard Open Geospatial Consortium (OGC) approved
formats, to normalize terrain data across Force Development simulations.

7 This section is based on presentations and a paper on the JTDS CB-TGS activity. Specifically, “Cloud

Terrain Generation and Visualization Using Open Geospatial Standards, Chambers and Freeman, 2014.
From proceedings of the Interservice/Industry Training, Simulation, and Education Conference.
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Figure: DoD C-TGS Architecture(Chambers and Sherman, 2014)
The above figure represents the implementation architecture for CB-TGS.
Implementation software represents a mix of commercial/proprietary and open source. At
the heart of the C-TGS are two data stores: A CDB structured data store and a 3d model
data store. All applications at the Visualization and Dissemination level interface the datastores via OGC service interfaces.
Connecting OGC Web Services to an open, simulation-optimized terrain data store, suchas a CDB structured data store, results in high-end performance for serving and rendering
geospatial content, the ability to dynamically modify terrain and support for all levels of
simulation. a high-end simulation system using CDB can dynamically update the terrain(such as a bomb crater) and have that dynamically updated terrain instantly served by the
Geospatial Discovery Service to any OGC compliant system, such as Esri® ArcMap,
QGIS, or a mobile web page. The underlying architecture and framework of the C-TGS
provide a mechanism to move high-end simulation to the point where data sharing,crowd-sourcing, and dynamic terrain are in-sync with GIS tools and simulation systemedits of the terrain repository.

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6.

Background and informative material

6.1
Intended Audience
The primary audience for the CDB standard includes distributed simulation systemdevelopers and synthetic environment database tool developers whose applications areintended to read and/or write synthetic environment database files. To this end, thisdocument discusses concepts incorporated in the standard and contains a detailed
description of the physical layout of the files as represented on disk.
6.2
Problem Definition
Complex mission simulators include a wide range of subsystems designed to simulate onboard equipment and to provide a rich gaming environment complete with weather,computer generated forces, ordnance, air traffic, networked players, etc. Each of thesesubsystems traditionally utilizes a proprietary runtime database (and format) for its
synthetic representation of the gaming area. These application-specific formats havebeen generated off-line at a database generation facility using a variety of tools andprocesses. This traditional approach to simulation has several inherent disadvantages,
including length of time needed for synthetic environment production for multiple
simulation applications, loss of correlation due to compilation differences, complexity inconfiguration management, and an inefficient update process. The abundance of distinct
database formats creates several challenges for configuration management, resulting inmismatched correlations, and in the increased timeline needed to generate these
databases. The CDB Standard specifies an approach that establishes conventions for all
simulator client subsystems (aka simulator client-devices). Further, the CDB Best
Practices provide detailed guidance on how to use a set of industry-standard formats.
The confluence of digital multispectral high-resolution satellite imagery, real time sensor
feeds, and highly capable visual systems has created dramatic new Mission Planning andMission Rehearsal capabilities. As a result, recent environment databases built to takeadvantage of these new capabilities require orders of magnitude more storage thanequivalent databases just a few years ago.
The CDB standard addresses these requirements through a common database model.
CDB is intended as a standard for use in producing a highly performant, unified synthetic
representation of the world. A data store built to the CDB Standard is referred to as a
CDB structured data store or CDB conformant data store. A CDB structured data store isa single-copy data repository from which various simulator client-devices are able tosimultaneously retrieve, in real-time, relevant information to perform their respective
runtime simulation tasks.
The CDB standard enhances unity and correlation between various simulator level clientdevices (e.g., Visual, Radar), while improving maintainability. As a result, one of themain benefits of the CDB standard is the elimination of several types of correlation errors
attributable to alternate, sometimes conflicting data representations required by each thesimulator client-devices. The CDB standard achieves this by allowing all simulator
clients-devices to share, in runtime, a single repository of the synthetic environment
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information. In addition, a CDB structured data store can also be used as a master
repository for the authoring tools. As a result CDB content can be interchanged between
data store workstations. Finally, in the case where one or more of the client-devices are
not compliant to the CDB standard, it is possible to revert to the conventional
compilation paradigm, (i.e., compile the CDB into one or more client-device loadable(usually proprietary) representations).
The actual storage formats of geospatial and model data in a CDB data store is based on
the native formats, such as TIFF, used by industry-standard toolsets. This eliminates thetime-consuming off-line database compilation process for each of the clients. The CDB
standard redefines a new balance between offline and online compilation processes
because modern computer platforms can now accomplish most of the compilation
process in real-time8.
The CDB standard addresses the issues that have characterized the simulation industry
for past decades (see Figure 1: CDB Approach to Synthetic Environment Generation), as
follows.
1. Size of Synthetic Environment Storage: The CDB standard specifies how to
consolidate the synthetic environment into a single data repository that provides astatic representation of the earth. This includes all the relevant information so that
all the simulator client-devices can perform their respective simulation tasks inorder to meet the training and mission rehearsal requirements. This approach
avoids any data content duplication. Storage intensive datasets can be optionallycompressed using modern third-party algorithms. The CDB standard provides afine-grained versioning scheme that avoids the replication of the entire DB wheneffecting small-area updates.
2. Scalability of Synthetic Environment Database: A CDB structured data store canbe built to a size or a density that far exceeds the capabilities of some or all of its
client-devices. The data structure defined by the CDB standard makes it possible
to implement runtime filtering schemes to adjust the loaded content density to thespecific capabilities of the client-devices. As a result, a CDB structured data store
can be scaled to take advantage of future simulator technological improvements.
3. Environment Data Store (DB) Correlation: Since CDB structured content is
unique (without data duplication), runtime source level correlation errors amongclients are eliminated, thereby ensuring inter-subsystem coherence and simulator
interoperability. In addition, it is possible to improve correlation by adjusting theruntime publishing process associated with each client-device.
4. Database Availability Timeline: The CDB data store generation process allows forsmall incremental updates, thereby shortening generation and build process times.
Furthermore, the translation step into a CDB structured data store is rather
straightforward since the industry-standard formats and encodings are used.

8

The CDB standard does require however, that most of its dataset be generated in a level-of-detailhierarchy.

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5. Configuration Management: Configuration management effort is reduced,
because a single CDB structured data store corresponds to the synthetic
environment of all the client-devices in the simulator. Furthermore, while a CDB
data store instance is conceptually a single, yet layered entity, the standard
specifies how incremental updates are performed resulting in efficient storage andhandling of CDB data store versions.

Figure 1: CDB Approach to Synthetic Environment Generation

6.3
Use of a CDB conformant data store as an Off-line Data store Repository
CDB can be used as a structured offline repository. This capability is described in Section
6.2 Volume 10 Implementation Guidance.
6.4
Use of a CDB conformant data store as a Combined Off-line and Run-time
Data store Repository
A data store conforming to this CDB standard can be both used an offline repository fordata store authoring tools or as an on-line (or runtime) repository for simulators. Thisapproach is described in Volume 10 Implementation Guidance, section 6.4.
6.5
Client-Device Independence
The CDB standard is client-device independent. The standard is based on a requirementthat all client-devices likely encountered on a tactical mission simulator need to besupported. The standard is completely independent of any vendor-specific devices.
6.6
Runtime Publisher
The runtime publishers provide the necessary level of abstraction. The level ofabstraction provided by the publishers is purely a function of the selected implementation
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Open Geospatial Consortiumof the client-device and its associated publishers. A client-device can “understand” andbe completely “aware” of a CDB compliant data store as defined by the CDB standard.
In this case, such a device would not require a runtime publisher, because it is already
CDB data store native.
The runtime publishers bridge the gap between the information content requested by theattached client-device and the information content and structure available to them in a
CDB conformant data store. As a result, the runtime publishers must each betheoretically “aware” of the following CDB concepts:
1. Tile: Ability to understand the concept of earth surface areas hierarchicallysubdivided in accordance to the CDB standard;
2. Level of detail: Ability to understand the concept of resolution or level-of-detail, forterrain, cultural vector data, raster imagery, and model geometry;
3. Terrain surface representation: Ability to understand concepts pertinent to earth
surface geometry and related attributes or properties;
4. Cultural vector data (point, linear, areal): Ability to understand the concept of point,
linear and areal cultural data and related attribution, fixed or conformed to earth
surface;
5. Grid-organized data and meshes: Ability to understand the concept of grid-organizedsingle-value datasets (e.g., elevation grid) and multi-value datasets (e.g., color
triplets);
6. Imagery: Ability to understand the concept of color raster imagery mapped onto
terrain surfaces or models;
7. Model geometry (incl. light points): Ability to understand the concept of generalsurface geometry;
8. Model positioning capability: Ability to differentiate between statically anddynamically positioned models;
9. Descriptive attribution: Ability to understand the attribution concepts pertinent to theclient-device.
6.7
Synthetic Environment Scalability & Adaptability
The concept of scalability when applied to synthetic environments not only applies to thegeographic extent of the data store but more importantly it also reflects the ability to scale
the environment in resolution and fidelity. These concepts are fully supported by the
CDB Standard and are explained below.
1. Geographic extent: Correspond to the range of geographic extent of the earth surface
that can be modeled.
2. Resolution: Correspond to the range of information density (for instance, the numberof elevation values per km2) of the modeled datasets.
3. Fidelity: Correspond to the amount and type of synthetic environment data that can bemodeled to support higher-fidelity simulator client-devices9. Consider for instance a
9

The CDB standard supports this concept through two mechanisms:

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simulator capable of supporting a single-surface earth skin representation versus one
capable of representing tunnels, bathymetric data, location-dependent tide heights,
location-dependent wave heights, etc. Clearly, the amount of information required by
the higher-fidelity simulator is greater.
4. Precision: Correspond to the range of numerical precision (i.e., number of bits
allocated to represent a quantity) of the modeled datasets.
Modelers face difficult challenges if they want a synthetic environment that is both
scalable and adaptive. The solution to this difficult issue extends beyond the“mechanics” of achieving backward/forward compatibility. The solution also requires acomplete “dissociation” of the data store from any constraints imposed by client-devices.
Current practice today is for modelers to repeatedly adjust the content, resolution anddensity of synthetic environment databases to closely match the capabilities andperformance of the targeted client-devices. When content is added to the database,previously modeled content is usually removed or simplified. Under such constraints it isdifficult for a modeler to build a synthetic environment database capable of meeting
anything but its immediate requirements.
Figure 2: Typical Evolution of a Database shows the evolution of a modeled region foruse in a mission rehearsal. The initial version of the region may have only a few highresolution/high-fidelity areas. However, over a given time period modelers will be asked
to model additional target areas. As a result, the size, complexity, resolution and fidelityof the synthetic environment database gradually increase. Without built-in provisions for
scalability, significant rework of the database is required each time a target area is added.

Figure 2: Typical Evolution of a Database

The CDB standard allows the “dissociation” of the synthetic environment database’s
extent, resolution, fidelity, precision, structure and format from client-devices. This
Data defaulting: The CDB standard is tolerant to missing data, because all attributes, layers anddatasets have Specification default behaviors. As more of the data is provided, the fidelity of theenvironmental database increases.
Additive layering: The CDB standard offers a layered environment database organization. The
layer organization is “fidelity-ordered”, (i.e., basic layers appear first in the hierarchy while the layers
needed for a higher-fidelity simulation appear later in the hierarchy).

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concept is not limited to aspects of formatting, numerical representation, internal
structure, file structure, file systems, etc. More importantly the concept also covers
aspects relating to synthetic environment database fidelity and resolution. Historically,
the fidelity and resolution of synthetic environment databases has been intimately linked
to the capabilities of the targeted simulator client-devices. More often than not, thesource data was manipulated and adapted to constraints imposed by the client-devices.
As a result, the content, resolution and density of synthetic environment databases wererepeatedly adjusted to closely match the capabilities and performance of the targetedclient-devices. The amount of time devoted to repeatedly adding/editing/removing
content, and then repeatedly re-publishing would largely exceed the effort of creating andbuilding the original synthetic environment database. The CDB standard offers themeans to break this inter-dependence.
When assembling a CDB conformant data store, the synthetic environment databasemodeler is permitted (within their time-cost budget) to include content that significantly
exceeds the capabilities of their simulator(s). The job of “adjusting” content to clientdevices is relegated to the runtime publishers; the modeler is freed from this laborintensive, repetitive task.
In a typical CDB data store implementation, it is anticipated that client-devices will
independently control their respective runtime publishers so that the runtime publishedsynthetic environment corresponds to their inherent capabilities (resolution, fidelity, etc.).
Nonetheless, the runtime publishing paradigm offers interesting new possibilities. For
instance, it would be possible to individually adjust the fidelity and resolution of thesynthetic environment for each client-device; this adjustment could be done at any time.
As a result, it is possible to control and adjust the overall simulator fidelity andcorrelation to a level that was previously unachievable.
The CDB standard does not enforce a particular computer hardware infrastructure. The
selected infrastructure allocated to the handling of a CDB data store is largely determinedby the overall simulation requirements. Any leeway the simulator architect may have attheir disposal when trading-off various simulator performance parameters against eachother, are as follows:
1.
2.
3.
4.
5.
6.
7.
8.

Geographic extent
SE/Simulator Resolution
SE/Simulator Fidelity
SE/Simulator Precision
Desired level of client-devices correlation
Client-level SE load management
Simulated aircraft speed
CDB sharing

An experienced simulation engineer can typically undertake this analysis. However, theprocess requires a good understanding of the content available in the targeted CDB
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structured databases and of the content each client-device needs in order to meet thestated level of performance and fidelity.
Alternately, it is possible to implement a simulator with client-devices (or attachedpublishers) that are capable of automatically adjusting resolution and fidelity in order toovercome performance limitations attributable to the CDB storage infrastructure and/or
runtime publishers.
Figure 3: Typical Implementation of the CDB standard on High-end Simulator provides asystem block diagram of a typical implementation of the CDB standard on a high-end
tactical flight simulator. The runtime CDB system serves the combined needs of a
mission functions computer, an OTW/NVG IG, a Forward Looking Infrared (FLIR) IG,
Radar and a Computer Generated Forces (CGF) subsystem equipped with its own terrain
server. The runtime CDB data store system is scaled to reflect the collective capabilitiesof the attached client-devices; as a result, the storage system is configured to supply thenecessary bandwidth. Similarly, the IO bandwidth of the CDB data store servers andprocessing performance of the runtime publishers are scaled to satisfy the demands oftheir respective client-devices.

Figure 3: Typical Implementation of CDB Standard on High-end Simulator

Figure 4: Typical Implementation of CDB Standard on Desktop Computer shows amodest application of the CDB standard. This approach consists of a single desktop
computer equipped with both stealth viewer and radar simulation application software.
Each application is front-ended by a runtime publisher that in turn interfaces to the CDB
data store via a standard file system. Given the more modest platform resources, some19
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trade-offs in either resolution or fidelity might be required. This can be implemented in
the runtime publisher or in the client-device application software.

Figure 4: Typical Implementation of CDB Standard on Desktop Computer

6.8
Simulator Wide Unique Data Representation
A CDB data store is a single repository for the entire simulator’s synthetic environment
data store (aka DB). The internal structure ensures that all datasets are uniquely
represented yet available (through a publishing process) to each of the simulator clientdevices at runtime. This paradigm eliminates the extensive duplication of datasets thatare shared by two or more client-devices.
The CDB standard is technically a normalized data storage model in the sense that it best
meets the logical data design objectives of correctness, consistency, simplicity, nonredundancy and stability. Ignoring any tailoring or tuning for particular application
requirements or performance, a normalized design provides the following advantages.
1. Minimize amount of space required to store data: Normalization precludes
storing data items in multiple places.
2. Minimize risk of data inconsistencies within the data store: Since datasets are
stored in only one place, there is no risk of datasets becoming inconsistent(uncorrelated).
3. Minimize possible update and delete anomalies: A normalized CDB data store
eliminates the concerns related to update or delete operations.
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4. Maximize the stability of the data structure: The process of normalization
helps in associating attributes with entities based on the inherent properties ofthe data rather than on particular application requirements. Thus, newapplication requirements are less likely to force changes to the CDB
model/data store design.
6.9
Key Benefits of the CDB Standard
The following outline the key benefits of using the CDB standard.
6.9.1 Improved Synthetic environment Data Store10(DB) Generation Timeline
Important reductions in both the DB generation and DB update timeline are expectedfrom an implementation of the CDB standard because of the following.
1. There is no need to compile distinct synthetic environment runtime datastores for each of the simulator client-devices.
2. All of the datasets common to two or more client-devices need not be
duplicated. All associated client-specific structures are also eliminated.
3. Tiles and layers are technically independent from each other; as a result,
there is no need to reprocess neighboring tiles and coincident layers.
However, one exception to this relates to the level-of-detail generation.
4. The tile structure permits users to “pipeline” or overlap the DB
creation/update process, see Figure 5: Pipelined DB Update Process, with
DB transfer process11.

Figure 5: Pipelined DB Update Process

5. The tile structure lends itself naturally to the concurrent or “parallel”
production of the CDB data store.
6. The internal versioning mechanism lends itself well to CDB structured
data store updates because only the affected tiles or layers need be retransmitted to the simulator. This represents a significant timesaving,

10 Please note that in earlier versions of the CDB standard that the acronym “DB” was used. As DB cases

confusion regarding whether CDB defines a database or not, the OGC CDB standard uses the term “datastore”. However, for the sake of backwards compatibility, the use of DB remains in this document.
11
Assuming the DB toolset (used by the modelers at the DB Generation Facility) allow its users tomanipulate Environmental DB content on a small-area basis.

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especially in cases where small updates are constantly applied to acomparatively large CDB structured data store.
7. The conversion of the synthetic environment from its tool-native
representation into a form directly entered by each of the simulator clientdevices is broken down into several publications accomplished in realtime on behalf of each of client-device. This approach permits the CDB
standard representation of the synthetic environment to be “dissociated”
from the resolution, fidelity, precision, structure and format imposed byeach client-devices.
6.9.2 Interoperable Simulation-Ready Synthetic environment Data StoreA CDB compliant data store is a fully interoperable, simulator-ready synthetic
environment DB, (i.e., it can be used “as-is” on any CDB-compliant simulator). Because
the data store is free of any simulator dependencies, there is no need to undertake a timeconsuming and expensive rework of the runtime data store(s) in order to adapt it (them)to the format, structure, content, and precision constraints imposed by the simulator.
6.9.3 Improved Client-device Robustness/Determinism
The CDB standard tile organization provides the means to implement deterministic
loading and/or paging of the data store because each tile corresponds to the same amountof data (i.e., a “quanta” of information called a LOD-tile), regardless of its position onearth and regardless of its assigned LOD. This is a key characteristic of the CDB
standard and is necessary to ensure deterministic operation of client-devices, even when
the data resolution varies considerably from region to region or when the data is modeled
at an extremely high-resolution. It is quite straightforward for a client-device todetermine the amount of memory it must locally allocate when loading (or paging-in) a
geographical area of interest. If the geographical area of interest exceeds the clientdevice’s capabilities, it can easily revert to a coarser LOD, hence gracefully degrading, as
opposed to aborting (due to an internal failure in allocating sufficient memory) or“skipping” over the offending area.
The tile organization lends itself to robust, deterministic management of memory withinclient-devices because memory can be allocated/de-allocated in fixed sized quantities.
As a result, client-devices need not concern themselves with complex and nondeterministic memory de-fragmentation schemes that do not lend themselves to real-time
applications.
6.9.4 Runtime-Adjustable Synthetic Environment DB Correlation and Fidelity
The CDB standard plays a critical role in improving the internal correlation of a synthetic
environment because it eliminates the replication of runtime data stores for each of theclient-devices. The prior art in simulation mandated replicated copies of the synthetic
environment data store. Each copy was constrained by the content, formats, andstructures specific to each client-device. As a result, the potential for correlation errors
abounded. The CDB standard resolves this issue by defining a single, usable in real-time,
open, synthetic environment data store representation.
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The “runtime publishing” paradigm now permits the simulator vendor the means to not
only control client-device load but to globally re-examine and control the level ofcorrelation within a simulator (or across simulators). While the CDB standard does notprovide explicit jurisdiction over the implementation of this mechanism in the clientdevices and/or publishers, it is nonetheless possible to improve parametric correlation, at
runtime, via control of the client-devices/publishers.
This topic is discussed in more detail in the OGC CDB Best Practice, Volume 1 Section
1.6.6 , Synthetic Environment Database Correlation.
6.9.5 Increased Synthetic Environment Data Store Longevity
The longevity of synthetic environment databases for use in simulation has traditionallybeen a source of considerable aggravation within the user-community.
Traditionally a considerable level of effort (both human and machine) was required toadapt source-level data to a form that is directly usable by each of the simulator clientdevices, also known as the runtime-level vendor-specific database format; this is referred
to as the “compilation” process. More often than not, the source data is manipulated andadapted to constraints imposed by one or more simulator client-devices. In most cases,
the content, resolution and density of synthetic environment databases are repeatedly
adjusted to closely match the capabilities and performance of the targeted client-devices.
While it is true that the native tool format database remains independent of the targetedclient-devices, it is clear that content of the source-level database roughly corresponds tothe capabilities of the then-current client-devices. As a result, source-level databases
become quickly outdated and do require a complete rebuild to take advantage of new
simulator capabilities.
The CDB standard avoids these pitfalls because the model does not need to be adapted tothe constraints imposed by simulator client-devices; that role is relegated to the runtime
publishers. Hence, the synthetic environment a CDB data store can be built, right fromthe start, to a level of fidelity commensurate with the anticipated useful life of thetargeted simulator(s).
6.9.6 Reduced Synthetic Environment Data Store Storage Infrastructure Cost
For equivalent synthetic environment content, the CDB standard offers a significant
storage space savings and significant reductions in the required interconnect
infrastructure to supply the synthetic environment data to the simulator(s).
The reduction in equipment and labor can be attributed to the following features.
1. Simulator-wide unique data representation: eliminate duplication ofdatasets across client-devices.
2. Compression of storage-intensive datasets: provides effective compressionof key datasets.
3. Fine-grain versioning: A CDB structured data store is internally versioned.
It is possible to revert to prior representations of the SE without restoring
stored back-ups of the data store. Because the underlying mechanism is23
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fine-grained, only in affected geographic areas or datasets of the data store
need to be versioned.
6.10 CDB Model Overview
The following sections provide a general description and focus of the CDB standard.
6.10.1 CDB Standard Data Representation and Organization
The CDB standard provides the means of describing all feature sets relevant to simulation(such as terrain and 3D objects). These feature sets are logical re-groupings of datasetsthat are used directly by the simulator client-devices.
The standard currently supports the following representations.
1. Terrain: A representation of the terrain shape/elevation, raster imagery, surface
attribution and other surface characteristics relevant to distributed simulations.
2. Point feature: A representation of a single location in space or on the earth’s surface.
A Point feature consists of a single <latitude, longitude> coordinate with or without
an elevation. When a point feature does not have an elevation, it is deemed to be on
the surface of the earth. The information includes point-feature type identification,
location, orientation, connectivity, attribution and other characteristics relevant tosimulation.
3. Linear feature (aka LineString): A representation of predominantly man-made multisegmented line-oriented features conformed relative to the terrain (such as runways,
roads, transmission lines, fences). The information includes linear feature typeidentification, location, orientation, lineal geometry, connectivity, attribution andother surface characteristics relevant to simulation.
4. Areal feature (aka Polygon or area): A representation of closed area features
conformed relative to the terrain such as forested areas and fields. The information
includes areal feature type identification, location, orientation, 2D geometry,
connectivity, attribution and other surface characteristics relevant to simulation.
5. 3D cultural model (aka Built Environment): Is a model that is statically positioned on
the terrain or bathymetry skin. Cultural models are often a 3D representation of aman-made or a natural object positioned and conformed relative to the terrain. The
information includes its geometry, articulations, raster imagery (texture, normal map,
light map, etc.), lighting systems, and other characteristics relevant to simulation.
6. Moving model: A model that is not fixed at one location in the synthetic environment
data store. The simulation host can update the position and orientation of a moving
model at every simulation iteration cycle. A moving model is a 3D representation ofman-made objects free to move within the data store. The information includes
feature type identification, (vehicle class, type, model, etc.), geometry, articulations,raster imagery (texture, normal map, light map, etc.), lighting systems, connectivity to
special effects, attribution and other characteristics relevant to simulation
7. Materials: A symbolic representation of the surface materials for all of the elements
contained within the data store. Client-devices are required to simulate the synthetic
environment over different portions of the electromagnetic spectrum: IR (e.g., FLIR,
NVG), microwaves (e.g., Radar), audio (e.g., Sonar), etc. The fidelity of the sensor
synthetic environment simulation model that runs in each of the client-devices is
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highly dependent on the richness and completeness of properties that characterize thesynthetic environment data store in the electromagnetic spectrum of interest12.
8. Navigational data: A representation of ARINC-42413 and DAFIF14 data in the form of
NAVAIDs, Airport/Heliport, Runway/Helipad, Waypoints, Routes, Holding Patterns,
Airways, Airspace, etc.
In order to represent the above feature sets, the CDB standard logically organizes its data
in mutually exclusive datasets. Furthermore, the CDB standard is platform and clientdevice independent. As a result, the internal data representation is free of client-device
specifics and more closely aligned to DB structures/formats supported by prominentindustry standard tools.
6.10.2 CDB Standard Logical Structure
The CDB standard is a structure for simulation and as such its storage structure is
optimized for simulator client-devices runtime performance. Therefore, the internal
storage structure is designed with these specific considerations in mind.
1. Promotes efficient real-time data access by the simulator client-devices without
degrading their performance.
2. Allows simultaneous accesses by all of the various simulator client-devices.
3. Promotes efficient data store updates and deployment in order to reduce thedeployment of a CDB structured data store onto one or more simulators.
To address these objectives, the storage structure geographically divides the world into
tiles (bounded by latitudes and longitudes), each containing a specific set of features(such as terrain altimetry, vectors), models, which in turn are represented by the datasets(see Figure 6: CDB Standard Tile/Layer Structure). The datasets define the basic storage
unit used in a CDB structured data store. The geographic granularity is at the tile level
while the information granularity is at the dataset level. As a result, the storage structure
permits flexible and efficient updates due to the different levels of granularity with which
the information can be stored or retrieved. At the data store generation facility, it is12

One of the primary objectives of this standard is to provide and integrate all of the data required by all
sensor devices, not just IGs producing the Out-The-Window (OTW) scenes. In addition, the mandate ofthis standard is to accomplish this objective in a device-independent fashion. The CDB standard provides ameans for client-devices to retain their internal Sensor Synthetic Environment Model (SEM), and yet do so
without introducing device dependencies within the CDB synthetic environment. To accomplish thisobjective, client-device vendors must provide the appropriate SEM properties for the prescribed CDB BaseMaterials (see Appendix L), since none of the (vendor/device-specific) material properties are stored within
the CDB
13 ARINC 424 or ARINC 424 Navigation System Data Base Standard is an international standard fileformat for aircraft navigation data maintained by Airlines Electronic Engineering Committee and publishedby Aeronautical Radio, Inc. The ARINC 424 specifications are not a database, but a "standard for the
preparation and transmission of data for assembly of airborne navigation system data bases"
14 Digital Aeronautical Flight Information File is a comprehensive database of up-to-date aeronautical data,
including information on airports, airways, airspaces, navigation data and other facts relevant to flying in
the entire world, managed by the National Geospatial-Intelligence Agency (NGA)

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possible to effect small updates, either at the tile level; the feature set level or the dataset
level. Similarly, the storage structure fully supports real-time retrieval of content at thetile level and the dataset level. Finally, the incremental versioning mechanism allows
users to efficiently deploy updates to a data store; only the files whose content differsfrom a prior version need be generated and transferred from the data store generation
facility to the simulation facility.
Another benefit of the CDB standard storage structure is its ability to support concurrent
generation and deployment.

Figure 6: CDB Standard Tile/Layer Structure

6.10.3 Tile/Layer/Level-of-Detail Structure
The CDB standard offers a structure that is well suited for the efficient access of its
contents. To this end, it relies on three important means to organize the synthetic
environment data:
•
•
•

Tiles
LayersLevel-of-Detail (LOD)

6.10.3.1
Tiles
The CDB standard defines a top-level tile structure designed to organize the data for
efficient access in real-time. The tile structure provides an effective means for simulator
client-devices to access the datasets of a geographical area at a selected LOD. Since thespatial dimension of tiles varies inversely with LOD (i.e., resolution), client-devices canreadily predict the amount of data contained within the tile; as a result, the managementof memory within client-devices is simplified and much more deterministic.

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The CDB standard Conceptual Model is logically organized as a strip of geo-unit aligned
tiles along each earth slice. Each earth slice is divided into a decreasing number of tiles
to account for the fact that the length of an earth slice decreases with increasing latitude.
6.10.3.2
LayersThe CDB model is also logically organized as distinct layers of information. The layers
are theoretically independent from each other, (i.e., changes in one layer do not imposechanges in other layers).
Layers are additive in fidelity, (i.e., the achievable level of the simulation fidelity
increases with the number of layers).
Secondly, unavailable layers are automatically defaulted. A database modeler need not
fully populate a CDB structured data store. There is no mandatory “coveragecompleteness requirement” imposed by the CDB standard. This feature permits thegeneration of a CDB conformant data store even when database modelers are confronted
with limited data availability. The usefulness/faithfulness of the synthetic environment
increases with the number of available layers.
The layering mechanism improves the efficiency of the client-devices since they need
only access (and be aware) of the datasets that are relevant to them, at their prescribed
level of fidelity. For instance, a simulator CGF client-device will not likely have a reason
to use ground raster imagery. However, it is quite likely interested in accessing groundsurface properties when determining traffic-ability.
6.10.3.3
Levels of Detail (LOD)
Level of detail (LoD) is a concept available in various disciplines from computer
graphics and cartography to electrical circuit design. For GIS practitioners, the disciplinewhere level of detail is most relevant and well known is 3D city modelling. In the CDB,
LOD is a mechanism for allowing increasing levels of fidelity without impacting system
performance. In CDB data stores, LODs are also an integral part of the physical databasestructure. The LOD requirement for simulation systems is similar with regard torequirements for increased fidelity in 3d City Models and standards such as CityGML.
The availability of LOD representations is critical to real-time performance, especiallywhen dealing with grid-organized data. Most simulation client-devices can readily takeadvantage of a LOD structure because, in many cases, less detail/information is necessary
at increasing distances from the simulated object. As a result, many client-devices can
reduce (by 100-fold or more) the required bandwidth to access synthetic environment
data in real-time.
Additionally, the availability of LODs can be readily exploited by simulator clientdevices to improve algorithmic efficiency. Devices such as Image Generators (IGs) canreadily take advantage of an LOD structure because image perspective naturally reduces
image detail with distance as a result of the perspective computation inherent to the IG.
As a result, much less geometric detail and texture detail need be processed or considered
at far range.
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The spatial sampling of each successive LOD in a CDB data store follows power of two
progressions. This is a prerequisite for the efficient and deterministic management ofmemory by all client-devices of a typical simulator.
The terrain LOD can be controlled to the tile level. Since the CDB standard specifies avariable LOD hierarchy spanning up to 34 levels, it is possible to control the allocation of
LODs by area. The variable LOD hierarchy provides for efficient use of storage because
the LOD hierarchy needs to be deepened only in the areas where higher resolution isdesired. Figure 7: Variable Allocation of LOD, illustrates an earth strip made up of aseries of tiles; some portions of the strip have been modeled with 3, 4, or 5 LODs
according to the application requirements.

Figure 7: Variable Allocation of LOD
6.10.4 CDB Structure, Organization on Media and Conventions
This CDB standard along with the CDB Best Practices describes the data content,
representation, as well as the logical organization of the data stored in the data store:28
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1. The Data store structure comprises all of the data structures used to access data store
content (such as file paths, Level-of-Detail (LOD), lists) to speed up access,information layering, versioning and configuration management; and2. Naming Conventions: Used to describe a naming hierarchy for cultural models,moving models, lights and model components.
6.10.4.1
Other Applications of the CDB Standard
While the CDB standard was initially targeted primarily for use in Special Operations
simulator applications, it is entirely suited to a broad range of other applications thatmake use of the same datasets; these include (and are not limited to):
1.
2.
3.
4.
5.
6.
7.

Ground warfare simulation
Anti-submarine warfare
Visualization
Modeling and Simulation
Urban Planning
Natural Resource Management
Emergency Management

The implementation of the CDB standard on legacy simulator client-devices usually
mandates the use of the runtime publishers. These costs are largely offset by the
consolidation (and substantial reduction) of storage and associated infrastructure. In the
future, it is anticipated that the runtime publishing computer infrastructure will be largely“absorbed” by higher performance client-devices that will natively process the data store
without an intermediate conversion into a legacy internal format.
In applications that are less demanding than flight simulation, the CDB standard can be
implemented without resorting to high-performance computer platforms. For instance,
the simulator repository mass storage system (shown in Figure 8: Typical CDB
Implementation on a Suite of Simulators) can be a single disk storage device. In
demanding applications, the simulator repository can be implemented as a large-scale
Storage Area Network (SAN). Similarly, the Update Manager IUM), the CDB server andeach of the client-device runtime publishers can be implemented as software tasks within
a single computer platform, or can even be migrated to software tasks running internallywithin the client-devices. Figure 4, Typical Implementation of CDB Standard on Desktop
Computer, illustrates a desktop trainer consisting of a stealth viewer15 and radar
simulations, implemented as software applications running on a single computer
platform; both applications pull their synthetic environment data from a disk-resident
CDB.
6.10.5 Use of CDB in Applications Requiring Dynamic Synthetic Environments
A CDB-compliant simulator already incorporates most of the architectural features
required to support the handling of Dynamic Synthetic Environments (aka DSE). Figure
15 A ‘stealth viewer’ is analogous to a camera viewpoint that is not ‘attached’ to any physical entity in asimulation

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1-14, Versioning Paradigm Applied to Dynamic SE, illustrates how CDB-compliant
simulator architecture can be extended to permit the runtime modification of the CDB.
This can be accomplished by leveraging simulator architectures that natively adhere to
the CDB data schema and to the CDB versioning capabilities.
This capability requires that the simulator be equipped with a Dynamic Synthetic
Environment Generator whose interfaces conform to the CDB standard; all otherelements of the simulator architecture are identical to those of a CDB-compliant
simulator.
Two applications of this principle could be envisaged.
1. DB update from DIS: This is the so-called “Dynamic Terrain/Synthetic
Environment”, where a group of confederates interoperate over a DIS
network by receiving update commands that trigger runtime modificationof the CDB.
2. DB creation/update from live data feed: Terrain areas could be created or
modified on-the-fly, based on live data (such as terrain imagery or LIDAR
data transmitted by a UAV) and provided instantly to the confederates.

Figure 8: Versioning Paradigm Applied to Dynamic SE

6.10.6 Synthetic Environment Data Store Correlation
Please read section 1.6.6 of the OGC CDB 3.2 Best Practice for additional details on
correlation https://portal.opengeospatial.org/files/?artifact_id=61935.

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Annex A: Revision history

AuthorParagraphmodified

Description

10/20/15

C. ReedManyFirst major “scrub”

11/20/15
2/20/2016

C. ReedMany
D Graham and Many
C ReedPrepare for first publication
Prepare for OAB Review

4/3/2016

D Graham

Prepare for RFC

5/18/2016

C. ReedMinor edits

Figures.

10/5/2016 1.0

C. ReedVarious edits

Preparation for publication as an
official OGC BP

11/20/2016 1.0

C. ReedVariousEdits for publication

1/21/2017 1.0

C. Reed1/16/2018 1.1

C. ReedDate

ReleaseReady for publication – add
references
VariousMinor corrections to typos.

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Annex B: References
This table lists the documentation referenced throughout this document.

Re

Title

Description

1

ARINC Standard 424-16

Navigation System Data Base, Aeronautical Radio Inc., August 30,
2002.

2

ASTARS-04 CDB

Systems Requirements

3

Digital Geographic Information
Exchange Standard (DIGEST),
Standard V2.1

The document can be obtained at the following address:
http://www.digest.org/

4

Enumeration and Bit Encoded
Values for use with Protocols
for Distributed Interactive
Simulation Applications.

This is document SISO-REF-010. It accompanies IEEE Std 1278.11995 and can be obtained from the Simulation Interoperability
Standards Organization at http://www.sisostds.org/

5

Extensible Markup Language(XML) 1.0 (Third Edition)

Bray, Tim, et al.
http://www.w3.org/TR/2004/REC-xml-20040204/
W3C Recommendation, February 04, 2004.

6

Guide - PD6777, BSI's Guide
to the practical implementationof JPEG 2000

The document can be found at:
http://www.jpeg.org/

7

IEEE Standard for Distributed
Interactive Simulation Application Protocols

IEEE Std 1278.1-1995

8

JPEG 2000: Image
Compression Fundamentals,
Standards and Practice

Kluwer International Series in Engineering and Computer Science,
Secs 642, by David S. Taubman and Michael W. Marcellin

Other useful sites include:
http://en.wikipedia.org/wiki/SRGB_color_space
The document is targeted at managers; application softwaredevelopers and end-users who want to know more about JPEG 2000.

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9

MIL-STD-2411 Raster ProductFormat Specification

The Raster Product Format (RPF) is a standard data structure forgeospatial databases composed of rectangular arrays of pixel values(e.g., in digitized maps or images) in compressed or uncompressed
form. RPF defines a common format for the interchange of rasterformatted digital geospatial data among DoD Components.
Department of Defense Information Technology Standards Registry
Baseline Release 04-2.0.
http://earthinfo.nga.mil/publications/specs/printed/2411/2411_RPF.pdf

10

MIL-C-89041 Controlled
Image Base Specification

Controlled Image Base (CIB). This Specification provides
requirements for the preparation and use of the RPF CIB data. CIB
is a dataset of orthophotos, made from rectified grayscale aerial
images.
http://www.fas.org/irp/program/core/mil-c-89041-cib.htm

11

OpenFlight Scene Description
Database Standard, Version
16.0, Revision A, November
2004, Presagis Inc

The original document has been annotated by CAE to create the
CDB-annotated OpenFlight Standard.

12

Product Standard for the
Digital Aeronautical Flight
Information File (DAFIF),
Eight Edition, Doc. #PS/1FD/086

National Imagery and Mapping Agency (NIMA), April 2003.

13

SEDRIS™ - Synthetic
Environment Data
Representation Interchange
Specification

The Source for Synthetic environment Representation andInterchange.
http://www.sedris.org

14

Shapefile Technical
Description - an ESRI White
Paper—July 1998

The original document has been annotated by CAE Inc to create the
CDB-annotated Shapefile Technical Description.

15

The SGI Image File Format,
Version 1.00, Paul Haeberli,
Silicon Graphics Computer
Systems

This specification can be found at:
http://paulbourke.net/dataformats/sgirgb/sgiversion.html

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16

TIFF rev 6.0 Adobe Developers
Association, Adobe Systems
Incorporated, 1585 Charleston
Road and P.O. Box
7900Mountain View, CA
94039-7900

A copy of this original standard can be found at:
http://partners.adobe.com/public/developer/en/tiff/TIFF6.pdf
and at:ftp://ftp.adobe.com/pub/adobe/
DeveloperSupport/TechNotes/PDFfiles
The original document has been annotated by CAE Inc to create the
CDB-annotated TIFF Standard.

17

XML Schema Part 0: Primer
Second Edition

Fallside, David, Priscilla Walmsley.
http://www.w3.org/TR/xmlschema-0/
W3C Recommendation, October 28, 2004.

18

XML Schema Part 1:
Structures Second Edition

Thompson, Henry S., et al.
http://www.w3.org/TR/xmlschema-1/
W3C Recommendation, October 28, 2004.

19

XML Schema Part 2: Datatypes
Second Edition

Biron, Paul V., Ashok Malhotra.
http://www.w3.org/TR/xmlschema-2/
W3C Recommendation, October 28, 2004.

20

ICAO Airline Designator

List of ICAO Airline Codes,
http://en.wikipedia.org/wiki/Airline_codes

21

Radar Signatures and Relations
to Radar Cross-Section. Mr. P
E R Galloway, Roke Manor
Research Ltd, Romsey,
Hampshire, United Kingdom.

This document can be obtained at the following Internet address:
http://aircraftdesign.nuaa.edu.cn/lo/Ref/General%20Topics/radar_si
gnatures_and_relations_to_rcs.pdf

22

AN/APA to AN/APD Equipment Listing.

This document can be obtained at the following Internet address:
http://www.designation-systems.net/usmilav/jetds/anapa2apd.html#_APA

23

Radar Polarimetry Fundamentals of Remote
Sensing.
National Resources Canada.

This document can be obtained at the following Internet address:
https://www.nrcan.gc.ca/earth-sciences/geomatics/satellite-imageryair-photos/satellite-imagery-products/educational-resources/9275

24

RCS in Radar Range
Calculations for Maritime
Targets, by Ingo Harre.
Bremen,Germany. (V2.0-20040206).

This document can be obtained at the following Internet address:
http://www.mar-it.de/Radar/RCS/RCS_xx.pdf

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25

Decibels relative to a square
meter – dBsm. By Zhao
Shengyun.

This document can be obtained at the following Internet address:
http://radarproblems.com/chapters/ch06.dir/ch06pr.dir/c06p11.dir/c0
6p11.htm

26

MIL-C-89041

Controlled Image Base (CIB)27

MIL-STD-2411

Defense Mapping Agency, Military Standard, Raster Product Format
(RPF)

28

MIL-STD-2411-1

Defense Mapping Agency, Registered Data Values for Raster
Product Format

29

MIL-STD-2411-2

Defense Mapping Agency, Incorporation of Raster Product Format(RPF) Data in National Imagery Transmission Format (NITF).

30

IEEE Std 1516-2000

IEEE Standard for Modeling and Simulation (M&S) High Level
Architecture (HLA)31

RPR-FOM Version 2 Draft 17

Real-time Platform Reference (RPR) Federation Object Model(FOM)
This RPR-FOM maps the DIS standard to the HLA standard.
The document can be obtained from the Simulation Interoperability
Standards Organization at the following address:
http://www.sisostds.org/

32

MIL-PRF-89039 Amendment 2

Performance Specification Vector Smart Map (VMAP Level 0), 28
September 1999
http://en.wikipedia.org/wiki/Vector_Map
http://earthinfo.nga.mil/publications/specs/printed/VMAP0/vmap0.html

33

MIL-PRF-89033 Amendment 1

Performance Specification Vector Smart Map (VMAP Level 1), 27
May 1998

34

MIL-PRF-89035A

Urban Vector Map (UVMap), 1st August, 2002

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35

OneSAF Ultra High Resolution
Building (UHRB) Object
Model

OneSAF UHRB Object Model (Version 2.2, Document Revision E,
March 7th, 2008, Contract #: N61339-00-D-0710, Task Order: 28.)
http://www.onesaf.net/community/systemdocuments/v.3.0/Maintena
nceManual/erc/UHRB_2_Object_Model.pdf

36

OneSAF Ultra High Resolution
Building (UHRB) On-Disk
FormatOneSAF UHRB On-Disk Format Model (Version 2.2, Document
Revision E, March 7th, 2008, Contract #: N61339-00-D-0710, Task
Order: 28.)
http://www.onesaf.net/community/systemdocuments/v.3.0/Maintena
nceManual/erc/UHRB_2_On_Disk_Format.pdf

37

U.S. Department ofTransportation - Federal
Aviation Administration –Advisory Circular 150/5340-1J

Standards for Airport Markings, AC- 150/5340-1J, dated 4/29/2005

38

Federal Aviation
Administration – Aeronautical
Information Manual

Official Guide to Basic Flight Information and ATC Procedures,
dated 14th February, 2008

36
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