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~ ADVISORY GROUP FOR AEROSPACE RESEARCH & DEVELOPMENT

7 RUE ANGELLE, 92200 NEUILL Y-SUR-SEINE, FRANCE

AGARD CONFERENCE PROCEEDINGS 574

Digital Contntunications Systellls: Propagation Effects, Technical Solutions, Systents Design (Systemes de propagation numeriques: effets de la propagation, solutions techniques, conception des systemes)

Papers presented at the Sensor and Propagation Panel Symposium, held in Athens, Greece, 18-21 September 1995.

I

-~+~- NORTH ATLANTIC TREATY ORGANIZATION

Published April 1996

Distribution and Availability on Back Cover

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SISP-A Software Tool for Propagation Prediction

Prabhakar M. Koushik, Theodore S. Rappaport, Mansoor Ahmed, and Ning Zhang

Mobile and Portable Radio Research Group Bradley Department of Electrical Engineering

Virgi~ia. Tech, Blacksburg, VA- 24061 - .0350, USA

Abstract: Accurate modeling of radio propagation character­istics in and around built-up urban environments is vital to the successful functioning of ~urv~illance and tracking sys­tems utilizing wireless technology. A vast majority of the software tools currently available to military and civilian users are based on very simple models with fairly limited accuracy and are closed architectures. We discuss the design and development of a software tool that prov~des: a) a framework for modelers to incorporate new models and test their hypotheses, and b) system designers and planners to obtain the propagation characteristics in any environment. The interactive software executes on a workstation, uses topographic maps with building overlays to predict signal coverage and channel characteristics for user-specified antenna locations. Work is in progress to improve the accu­racy of the prediction software through better diffraction modeling.

I. INTRODUCTION

While aircraft surveillance has been used extensively for drug interdiction, it is expensive. A surveillance method that's cheap by comparison is tracking suspect cargo and vehicles by placing small hidden transponders on them, capable of relaying position data obtained by a hidden on­board GPS rec«?iver. In such circumstances, the antennas used may well be suboptimal, and it is crucial to know a pri­ori the best locations for beacons or receiving posts within a city to ensure reliable tracking of the suspect. A thorough theoretical understanding and modeling capability of radio propagation characteristics in and around built-up environ­ments is vital to the successful functioning of surveillance and tracking systems utilizing wireless technology. Accurate propagation models, based on real-world phenomena, are needed for rapid installation, hardware development, and spectrum utilization plans for future wireless communica­tion systems. This paper presents SISP, a software tool for propagation prediction and wireless system design.

Radio communication channels are subjected to varying conditions in which the signal travels from the transmitter to the receiver via multiple paths. The received signal strength can be small or large depending upon whether the signals combine destructively or constructively. Thus, it is impor-

tant to predict the spatial distribution of power, the interfer­ence, the propagation power loss, etc., to completely characterize the propagation environment.

Typically, measurements are made to determine the charac­teristics of the propagation channel. However, these require a partial installation of the system and are time consuming and expensive. Moreover, they cannot be used for determining the performance of the system in the presence of different ter­rains. Over the years, terrestrial communication systems have been installed using empirical or semi-empirical propagation models. While many experimental or theoretical models have been developed to predict radio propagation in land mobile systems, they are not general enough to characterize the dif­ferent propagation environments. Site specific propagation modelst which utilize information about the environment such as the terrain elevation and morphology of buildings, etc., hold great promise for accurate predictions in different environments.

Site specific propagation models typically utilize large data­bases of diverse site information. A software tool that facili­tates management of these databases can significantly ease the complexity of using them. The visualization of results generated by these models is also significant, since this pro­vides feedback to the user about the performance of the sys­tem. Besides, the software tool can be utilized to analyze and compare predicted and measured data which can be used for improving the accuracy of the propagation models.

SISP provides a flexible software platform for propagation prediction, performance ana~ysis, and efficient database resource management. The framework of SISP encompasses propagation prediction modules, the graphical user interface, a suite of display and analysis routines, and data pro~essing routines. The general framework of SISP is shown in Figure 1. The modular structure allows for rapid development, easy extensibility, and enhancements to the software. Section II of this paper discusses the resource organization of SISP and presents the various databases that are used. The principal component of SISP is the propagation prediction module which contains the routines that implement the various prop­agation models. Section III of the paper discusses the propa­gation models that SISP currently incorporates. The user

Paper presented at the AGARD SPP Symposium on "Digital Communications Systems: Propagation Effects, Technical Solutions, Systems Design", held in Athens, Greece, 18-21 September 1995 and published in CP-574.

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interacts with the propagation models through a robust and user frien~ly graphical interface. Section IV discusses the predictions of. the model and compares it to measured results. Section V summarizes the work done and states the objectives of the research effort currently underway.

II. RESOURCE MANAGEMENT

A significant hurdle in the use of site specific models is the diversity of data· formats in which the environmental infor­mation is available. A considerable amount of work has been done to establish and adopt standards for each type of data. The SISP database comprises terrain elevation data, building contour and elevation data, RF measured and pre­dicted dat~, and antenna patterns.

A graphical user interface provides the interactive frame­work of SISP. It furnishes the user with the capability to create and maintain a database of site specific information and establish a simulation environment. The user.can spec­ify transmitters and receivers at a particular point, or along a grid, or a track. Parameters such as transmitter power, fre­quency of operation, height of antenna, etc. can also be entered via the graphical user interface.

In an outdoor microcell environment, terrain and buildings are the dominant surfaces that influence the transportation of energy. Accordingly, the details of the outdoor environ­ment need to be represented accurately in order for the models to provide accurate predictions. AutoCAD [1], a general purpose computer-aided design package is gener­ally used to describe the building data for propagation pre­diction purposes. The very general way of representing information in AutoCAD represents a significant proc~ss­ing challenge to the prediction routines. Our work has iden-tH1"".1"1., <'nh<"<>+ n.fr' A .. +.-.i("'A n c~~""·<-~~ "'·-~" :~ ~~·-~~~1 ~.-~-····'· ....... ""' ..... ~~ L...> l>JIL-->"-"'U..::JIL. 'V'J~ .d. t'.l1o'..I~V~.4 j\11.-# 1\1..~_;('•.'>\' .. l~_l~~~~.ld \',~\!~('~f ... l!.M t)\'_l.'UI.fJ"~.((~.!l ~J~!t~YUg~~

to r\:ipi~;;;cHt i:ho toiYUiil, Htorpho~ogy, outdoor building data­bases, and building floor plans while keeping the process­ing overhead on the propagation prediction routines to a minimum. Details on the Real World Database Format (RWDF) can be found in [2].

The terrain elevation map and the building contour map represent georeferenced data. The geodetic reference sys­tem used to reference the locations displayed can be speci­fied by the user. SISP primarily supports the Universal Transverse Mercator (UTM) coordinate system. This is a planimetric coordinate system and has the advantage of using linear decimal units for complete coordinate descrip­tions. This simplicity of notation offers greater precision and computational convenience. SISP also supports the Geographical Coordinate System (lat-long).

The terrain elevation data for SISP is obtained from the Digital Elevation Models (DEM) supplied by the· USGS [3]. The DEM's are available in 7.5' quadrangle coverage

and 1° quadrangle coverage. SISP utilizes the 7.5' DEM's, with a scale of 1:24,000. The 7.5' DEM consists of a regu­lar array of elevations referenced horizontally in the UTM coordinate system. The elevation data is stored in profiles in wh~ch the spacing along and between the profiles is 30m.

Th_e terrain data format in the SISP database conforms to the GRASS 4.0 raster data format GRASS (Geographic Resources Analysis Support System) is a geographic infor­mation system (GIS) designed and developed by the U.S. Army Construction Research Laboratory (USACERL) [4].

The General Data Format (<JDF) was developed, for SISP, to provide a standard data format for importing RF mea­sured and predicted data into the database. The GDF is an extensible machine independent ASCII format. It is modu­lar and changes, based on changing requirements, can be. easily accommodated. The primary objective in the design of this format is to provide a user editable data format for storing measurements made using various measurement systems.

· While GDF is suitable for providing a common format to represent RF measurement and prediction· data, it does not lend itself easily to analysis and visualization because of the sequential ordering of data sets that the format enforces and the significant quantity of extraneous descriptive infor­mation present in the file. For effective analysis and visual­ization of data, rapid retrieval is an important requirement. Hence, a indexed file structure that allows random access to the data sets is essential. The data stored in GDF is thus converted to a binary format called the Network Common­Data Format (NetCDF) [5].

III. P" OPAGATION MODELS

A few eKlOlpiR'ical m.odelis ~mch m; the m~pmmntiml pl1lth loss, and the Hata model have been incorporated into SISP to demonstrate the feasibility of the proposed architecture. The more complex site specific models are now being incorporated into the same framework. Site-specific models that take into account the physical characteristics of the environment are capable of providing more accurate pre­diction results than statistical models. By using the concept of ray tracing, energy transportation from a discrete point source can be represented by rays, and the interaction of the rays with objects in the environment may be modelled using well known concepts of transmission, reflection, and diffraction. This assumption is reasonably accurate at high frequencies when objects of interest in the propagation environment are far larger than the wavelength.

The signal in a microcellular environment can propagate to the receiver via multiple paths due to reflection, diffraction, and scattering of the radio waves by the objects in the envi­ronment. Using simplified geometric optics assumptions,

the prediction software launches and traces rays in three dimensions, and determines the path loss and propagation delay for each ray. The model determines the path through which the direct line of sight, specularly reflected, diffusely scattered, and diffracted rays arrive at a receiver. The received rays are then used to estimate the channel power delay profile and subsequently the path loss at the receiver location. Thus, ray tracing can help estimate not only the deterministic amplitudes of each type of ray, but also the exact time of arrival of the energy at a specific point in the coverage region. This may then be used to compute the sta­tistical frequency and time domain channel characteristics including path loss, and hence received signal strength (RSSI).

The transmitter is modeled as a point source generating rays uniformly in all directions. To model energy transfer correctly from the transmitter, it is necessary to launch rays at all possible angles of departure with a consta~t angular separation between rays. An elegant approach is to launch rays through the vertices of an icosahedron inscribed in an unit sphere, with each of its triangular faces subdivided into smaller triangles. This method for launching rays provides wavefronts of equal shape and area that can be easily subdi­vided as may be infered from Figure 2.

A brute force recursive technique is used to trace all the rays after they are launched from the transmitter so as to determine each ray path by which significant levels of energy radiated from the specified transmitter reaches a receiving point. Briefly, the prediction program performs the following:

Check the existence of a line of sight path for every receiver. If such a path exists, the path loss is calculated for the direct ray and the ray parameters are stored. If a direct path does not exist between the transmitter and the receiver, check if a diffracted ray can be received. If a valid diffrac­tion path exists, the received energy due to this path is cal­culated. To predict energy arriving at a receiver location due to specular reflection or scattering, rays are launched from the transmitter location and each ray is traced till it intersects an object. If no object intersects the ray, a new ray is launched from the transmitter and traced. If a ray intersects an object, a ray path is drawn from the point of intersection to the receiver. If this path is unobstructed, the .ray is tested for specular reflection. A reflected ray is received at a point if it lies within a reception sphere· around the receiver point. In case the received ray is not specular, it is considered to be a scattered path and the RSSI is com­puted accordingly. The reflected ray is now launched from the point of intersection and treated as a new ray. This recursion continues until a user specified number of ray object intersections has been exceeded. A new ray is then launched from the transmitter.

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The received power at any location is the vectorial sum of the multipath components of the LOS, reflected, diffracted, and scattered rays. The total field at a receiver is deter­mined by the coherent summation of the individual contri­butions of each ray. The following sections describe the individual effects of the multipath components.

A. Line of Sight (LOS) Rays

The path loss with respect to lm free space is directly cal­culated from the distance between the two points (d) using the relation

(3.1)

Path loss measurements were made in Rosslyn, VA to test the accuracy of the line of sight model. The predicted path loss for line of sight receiver locations were found to be 8 dB lower (typically) when compared to the measured path loss. Careful analysis of measured and predicted results showed that this difference could be explained by consider­ing ground reflections. It is known that the phase of the plane wave reflection coefficient, for both vertical and hori­zontal polarization at grazing incidence is 180 degrees. This would mean that the LOS signal and the ground reflected signal arriving at the receiver have a phase differ­ence of 180 degrees. Therefore for such cases the RSSI due to these two paths must be subtracted. Equation (3.2) indi­cates the new model.

ELOS oc (Efs -Etr) (3.2) where Ers is the free space field as calculated from Equation (3.1) and Etr is the field due to terrain reflection for low lying transmitters.

B. Reflected Rays

Specular reflection or reflection is characterized by the inci­dent and reflected rays making equal angles with the sur­face normal. Rays r1 and r2 in Figure 3 are reflected rays. The relationship of the reflected wave to the incident wave is given by

[~~ = RTDR[~~ (3.3)

where ErH and Erv are the horizontally and v~rtically J?Olar­ized components of the reflected wave and E1H and E1v are the horizontally and vertically polarized components of the incident wave. Matrix R is the transformation from verti­cally and horizontally polarized components to components perpendicular and parallel to the plane of incidence and is given by

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R = [cos8 sinel -sinS cosej

(3.4)

where e is the angle between the two sets of axes discussed above. The matrix D is given by

D = ra~ ;J (3.5)

where r ..L is the reflection coefficient for the wave with E­field in a direction perpendicular to the plane of incidence (perpendicularly polarized) and r ..L is the reflection coeffi­cient for the horizontally polarized wave. Both the reflec­tion coefficients depend on the angle of incidence and the material of the reflecting surface. The material dependence is limited to the relative permittivity ( Sr) of the material of the reflecting surface for dielectrics, particularly at high fre­quencies. This method of calculating the reflected' energy is based on the assumption that the reflection occurs at the interface between two infinite media.

A reception sphere around the receiver location is used to determine the reception of a specular reflected ray at the point. The radius of the sphere is directly proportional to the total path travelled by the ray and the angular spacing between neighboring rays at the source. Each ray represents the field in the solid angle radiating from the transmitter. If the t:ay after reflection from one or more surfaces intersects the sphere, it contributes to the total energy received at that location.

C. Scatt~red Rays (Rough Surface Scattering)

propagated in directions other than the specular direction. For receiver locations near a wall or a building surface where no specular component is predicted, energy due to the proximity of the surface is predicted by rough surface scattering. The bistatic radar (bistatic refers to the fact that the transmitter and receiver are at different locations) equa­tion may be used to model the scattered energy. The power received due to a scatterer (P 8) at a distance <4 from the receiver and rlt from the transmitter is given by:

2 P1G1Grcr'A

ps = 3 .2 2 . (3.6) (41&) atdr

where Pt is the transmitted power, Gt is the gain of the transmitter antenna, Gr is the gain of the receiver antenna, A. is the wavelength and a is the bistatic radar .cross section of the scattering object. The bistatic radar cross section is defined as the ratio of power density in the scattered signal in the direction of the receiver to the power density of the

signal incident on the scattering object [6].

The models for calculating the bistatic radar cross section of an object are applicable only in the far fields. At 900 MHz and a 10m wall, the far field is 667 m. Hence, the above models cannot be used directly to predict rough sur­face scattering in microcells where distances of about lm may be encountered. A heuristic approach [12] that divides a large surface into small facets so that the receiver is in the far field of each facet is used to apply these models. Scatter­ing in non-specular directions is then given by the non­coherent summation of power scattered form each of these facets. The geometry is shown in Figure 3. The size of the facets depends on the angular spacing between the rays at the transmitter and on the distance travelled by the ray to reach the scattering surface. To calculate the bistatic radar cross section of each of the facets the following equation is used:

2 4n (~x~y) crrcos8;

a; = 'A2 (3.7)

where e, is the angle the scattered ray makes with the specular direction, 6x and fly are the dimensions of the facet, A. is the wavelength and 0' r is an additional loss fac­tor. TJtis factor is added because most of the surfaces encountered are not perfectly conducting and the material of the surface must be used to calculate this factor.

D. Diffracted Rays

According to geometric optics, reflection, refraction and direct line of sight rays are the three basic mechanisms of energy propaga:: 111. The theory breaks down in shadow ... "'""""' ... " I ,1,..,..,;.., .. · · · ;.., ,. .. h,n , .. ..,.,"\ '~'h"r"" ""'ithPr ~ rlirPf't Alb>LJll.'6f.U.ll~ ,-..lo-.ll.6,!1.J!.44L ... ~LAlli. ..._"_,.,..,_.,..._<l-!I.A .__,.__,.,__...._~,_,.,., WII.U.U'<..Ja.'-' .,._.,._.,..,... .. .., ...... .,. --~ -~~-~--

ray nor a reflected nly is rccdvcd. \Vhcn a ll.'eceiver is heavily shadowed, a significant portion of the received sig­nal is due to energy diffracting over, or around the building edges. Diffraction supplements the geometric optics theory to determine non-zero field in shadow regions. It also elim­inates the sharp field transition that is observed between the shadow and lit regions by using GO. The geometrical the­ory of diffraction [ 1 0] extends geometric optics and intro­duces diffracted rays to account for energy received due to diffraction. Knife-edge and wedge diffraction has com­monly been used to account for diffracted energy. The extension of the single knife-edge diffraction theory to mul­tiple edges is involved and a number of approximations have been proposed [7][8][9]. Our software traces dif­fracterd rays in three dimensions. The field at any point is related to the angle of diffraction with the following model[12]:

(3.8)

(3.9)

where 9 is the angle of diffraction and k is the wave num­ber.

Iv.RESULTS

Predictions were made using the software described above and compared against actual measurements perfonned in Rosslyn, Va. Rosslyn is a typical urban setting with a wide diversity of building types. Further, the terrain elevation varied from !Sin to 55m over the area considered for the study. Figure 4 shows a projection of the area under study together with street names and the location of the transmit­ter. Figure 5 shows some of the results obtained.

V. CONCLUSIONS

In this paper, we have presented the structure and salient functional features of SISP. The software tool can be uti­lized in research for propagation prediction and wireless system design. We are currently working on improving the accuracy and the computational efficiency of the site spe­cific propagation model. Efforts are also being made to pro­vide an antenna library and improved visualization capabilities.

ACKNOWLEDGMENTS

The authors wish to acknowledge .the support of the Advanced Research Projects Agency (ARPA) for this project. The authors also wish to acknowledge the work ·of Kurt Schaubach, Scott Sei~el, and Joseph Liberti.

REFERENCES

[ 1] AutoCAD Release II, Reference Manual, Autodesk Inc., 1990.

[2] S. Sandhu, "Real World Database Fonnat - MPRG Internal Document, 1995.

[3] Digital Elevation Models-- Data Users Guide, Dept. of the Interior, U.S. Geological Survey, Reston VA, 1987.

[4] James Westervelt et al., "Introduction to GRASS 4.0," GRASS 4.0 Users' Manual, U.S. Army Construction Engineering Research Laboratory, Illinois, 1991.

53-5

[5] NetCDF User's Guide - An Interface for Data Access, Unidata Program Center, April 1993 ..

[6] C.A. Balanis, Advanced Engineering Electromagnet­ics, John Wiley & Sons, New York, 1989.

[7] K. Bullington, "Radio Propagation at frequencies about 30 Me", Proc. IRE, Vol. 35, No. 10, Oct. 1947, pp. 122-1136.

[8] '1. Deygout, "Multiple knife-edge diffiaction of microwaves", IEEE Trans. on Antennas and Propagation, Vol. AP-14, No.4, April19~6, pp. 480-489.

[9] J. Epstein and D.W. Peterson, "An experimental study of wave propagation at 850 MC", Proc. IRE, Vol. 41, No.5, May 1953, pp. 595-611.

[10] J.B. Keller, "Geometrical Theory of Diffraction", Journal of the Optical Society of America, Vol. 52, No. 2, Feb. 1962.

. [11] S. Sandhu, P. Koushik, T.S. Rappaport, "Predicted Path Loss for Rosslyn, VA. - second set of predictions", MPRG Technical Report for ORD, MPRG-TR-95-, March 1995. .

[12] K.R. Schaubach, "Microcellular Radio channel Pre­diction Using Ray Tracing", Masters Thesis, VPI&SU, MPRG-TR-92-15, Aug. 1992.

[13] M.D. Yacoub., Foundations of Mobile Radio.Engi­neering, CRC Press Boca Raton, 1993.

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Data Bases

Indoor lj Building 1....,_

Antennaslj-

-------1-4-t

I GUI

Resource Management

I

Post Processing Requestor

' Propagation

t

Prediction

Routines

---Measured,

Predicted, &

Processed Data

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I

SISP External Interface

External

-. Processing

Routines

Figure 1. SISP General Framework

~ ' Post

Processing

Routines

~ Optimization !

IR?.®l!II~finn®&~ I

(a )Rays launched by tessellating an icosahedron

(b) An icosahedron tessellated

with N=20

Figure 2. Rays launched through a tesselated icosahedron

scattering surface

Tx

-

small rectangular section

Rectangular area

proportional to area illuminated

by ray tube

Rx

Figure 3. Scattering model for flat surfaces

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U\

'-f 00

Figure 4 Tx. locations and street names fo2· path loss measurements in Rosslyn, Va.

t ;t ~ ·-, l-:,-

CJ-

iil ~ (/) -90 (/)

_g ..c: ca -100 a..

m ::!:!..

-110

-120

-130

-140 0

(/) -90 .9 ..c: £-100

-110

-120

-130

x : predicted

o: measured

10 20 30 Points along Moore St.

x : predicted

o: measured

-140~--------~--------~--------~ 0 20 40

Points along West 19th St.

-50

-60

-70

-so iii' :e. (/) -90 en 0

..J

..c ca -100 a..

-110

-120

-130

-140

m­::e.

0

-50

-70

-so

~ -90 ..J ..c 'ta-100 a..

-110

-120

-130

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x : predicted

o: measured

10 20 30 Points along Lynn St.

x : predicted

o: measured

-140~--------~----------~----~ 0 20 40

Points along East 19th St.

Figure 5. Comparison of measured and predicted path loss along streets in Rosslyn, Va.

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DISCUSSION

Discussor's name: K. Craig

Comment/Question:

Commercial site-specific ray trace models are available. Have any of these been included in the validation tests that you (and Professor Luebbers) referred to?

Author/Presenter's reply:

Not to my knowledge, although colleagues in the industry and government indicated to me that those are cruder models than the ones we are testing. I am not certain, however, your suggestion is a good one.

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DISCUSSION

Discussor's name: K. Craig

Comment/Question:

Is there a justification for only including non-specular effects at the final reflecting surface? Are not non-specular reflections between any two reflectors equally important?

Author/Presenter's reply:

Our belief is that the last leg of each ray, if it is not offering a specular reflected component, will be the main contributor to the scattering energy. Remember, Ell rays may offer this type of scattering signal, so the sum of many scattered ray energies will yield the scattered component. Our limited tests show this is very close to measured values, when the RSSI is very weak. However, there is no rigorous justification for this.

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DISCUSSION

Discussor's name: J. Harvey

Comment/Question:

1 . How many orders of reflection do you typically follow?

2. Could you comment on differences between your model and Professor Luebbers?

Author/Presenter's reply:

1 . Twelve are more than sufficient for 1 km x 1 km.

2. We use Bonding Volume Hierarchy and consider diffuse scattering on the "last leg" of each ray. We currently use a simpler wedge diffraction model, but have 3-D capability and polarization. We have a variable reception sphere and shoot out rays with a specified angle/spatial separation, as opposed to using Professor Luebbers' technique of specifying a number of rays which nearly guarantees receipt of ray types.

53-13

DISCUSSION

Discussor's name: A. Altintas

Comment/Question:

Did you test the sensitivity of your algorithm on the building model? What I mean is that, did you try the algorithm with the slight shifting or rotating of the buildings?

Also, you are developing a commercial code, in that case is it a good idea to use parallel processing techniques?

Author/Presenter's reply:

1. We have not rigorously tested this, although an interesting paper on this appeared in the 1995 IEEE Vehicular Technology Conference Proceedings from a European group. This is an important question since it impacts accuracy and resolution issues when running the models.

2. Parallel processing will be common place in a few years, we believe. Right now, it's best for use in the research laboratory.

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DISCUSSION

Discussor's name: E. Van Lil

Comment/Question:

How do you discriminate between the different buildings like concrete, aluminium, etc. Do you include this effect in your program or do you intend to do so?

Author/Presenter's reply:

Right now, we must manually choose to model each building with a specificEr .. We use a default value of concrete. Ideally, the photogrametry data base would have this information passed to the model via the data base.