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HindawiMathematical Problems in EngineeringVolume 2017, Article ID 8157319, 8 pageshttps://doi.org/10.1155/2017/8157319Research ArticleSimulation-Based Early Prediction of Rocket, Artillery,and Mortar Trajectories and Real-Time Optimization forCounter-RAM SystemsArash Ramezani and Hendrik RotheHelmut-Schmidt-University/University of the Federal Armed Forces Hamburg, Institute of Automation Technology,Chair of Measurement and Information Technology, Holstenhofweg 85, 22043 Hamburg, GermanyCorrespondence should be addressed to Arash Ramezani; [email protected] 30 January 2017; Accepted 2 July 2017; Published 7 August 2017Academic Editor: Marcello VastaCopyright 2017 Arash Ramezani and Hendrik Rothe. This is an open access article distributed under the Creative CommonsAttribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work isproperly cited.The threat imposed by terrorist attacks is a major hazard for military installations, for example, in Iraq and Afghanistan. The largeamounts of rockets, artillery projectiles, and mortar grenades (RAM) that are available pose serious threats to military forces. Animportant task for international research and development is to protect military installations and implement an accurate earlywarning system against RAM threats on conventional computer systems in out-of-area field camps. This work presents a methodfor determining the trajectory, caliber, and type of a projectile based on the estimation of the ballistic coefficient. A simulation-basedoptimization process is presented that enables iterative adjustment of predicted trajectories in real time. Analytical and numericalmethods are used to reduce computing time for out-of-area missions and low-end computer systems. A GUI is programmed topresent the results. It allows for comparison between predicted and actual trajectories. Finally, different aspects and restrictions formeasuring the quality of the results are discussed.1. IntroductionField camps are military facilities which provide livingand working conditions in out-of-area missions. During anextended period of deployment abroad, they have to ensuresafety and welfare for soldiers.Current missions in Iraq or Afghanistan have shown thatthe safety of military camps and air bases is not sufficient.A growing threat to these military facilities is the use ofunguided rockets, artillery projectiles, and mortar grenades.Damage with serious consequences has occurred increasinglyoften in the past few years.This paper focuses on mortars and rockets because theyare more and more used by irregular forces, where they haveeasy access to a large amount of these weapons. Furtherreasons are the small radar cross-section, the short firingdistance, and the thick cases made of steel or cast-iron, whichmakes mortar projectiles and rockets hard to detect anddestroy.The challenge is to establish an early warning system fordifferent projectiles using analytical and numerical methodsto reduce computing time and improve simulation resultscompared to similar systems. An appropriate estimation ofthe ballistic coefficient and the associated calculation ofunknown parameters is the central issue in this field ofresearch.Up to now, only a few approaches have been published.Khalil et al. [1] presented a trajectory prediction for thespecial field of fin stabilized artillery rockets. Chusilp et al.[2] compared 6-DOF trajectory simulations of a short rangerocket using aerodynamic coefficients. A very good overviewof modeling and simulation of aerospace vehicle dynamics isgiven by Zipfel [3].An et al. [4] used a fitting coefficient setting methodto modify their point mass trajectory model. Chusilp andCharubhun [5] estimated the impact points of an artilleryrocket fitted with a nonstandard fuze. Scheuermann et al.[6] characterized a microspoiler system for supersonic finned

Mathematical Problems in Engineeringprojectiles. Wang et al. [7] established a guidance and controldesign for a class of spin-stabilized projectiles with a twodimensional trajectory correction fuze. Lee and Jun [8]developed guidance algorithm for projectile with rotatingcanards via predictor-corrector approach. Fresconi et al. [9]developed a practical assessment of real-time impact pointestimators for smart weapons.This paper is based on Ramezani et al. [10]. Real-timeprediction of trajectories and continuous optimization is oneof the main aims of this work. With the aid of graphicalsolutions, it is possible to differentiate between several objectsand determine firing locations as well as points of impact.The goal is to provide active protection of stationary assetsin todayโs crisis regions. Therefore, a modern counter-RAMsystem with a clear GUI must be developed and will then beemployed for most threats.Cd2MaFigure 1: Characteristics of the air drag coefficient ๐ถ๐ .2. Ballistic ModelThe projectile is to be expected as a point mass: that is,the entire projectile mass is located in the center of gravity.Rotation is irrelevant in this case, so we regard a ballisticmodel with 3-DOF.The Earth can be regarded as a static sphere with infiniteradius and represents an inertial system. Based on an Earthfixed Cartesian coordinate system, the force of inertia isapplied in a single direction.Different projectiles have to be considered in order toset up a mathematical model. While rockets can be regardedas spin-stabilized projectiles, which have a short phase ofthrust and are particularly suitable for long distances up to20 km, mortar grenades are arrow-stabilized and fired onshort distances up to approximately 8 km.Other mathematical models for typical fin stabilizedartillery rockets are presented in [11โ16].2.1. Exterior Ballistics. The ballistic model is principally basedon Newtonโs law and the equations of motion are consideredto be under the effect of air drag and the force of gravityonly. Additionally, rockets have a thrust vector impelling theprojectile for a few seconds (generally, combustion gases havea velocity range of 1800โ4500 m/s [18]). Anyhow, rocketsas well as mortars have ballistic trajectories and the objectis to identify the threat on the basis of different flightcharacteristics. Let ๐ denote a reference acceleration (acceleration ofgravity at sea level on Earth), with 2 ๐ 9.80665 m/s ,(1)taking effect on the point mass in vertical direction. The air drag ๐ท can have different values, depending onthe design of the projectile, that is,(i) muzzle velocity V0 ,(ii) weight,(iii) aerodynamics,and the properties of air, for example,(i) density,(ii) temperature,(iii) wind,(iv) speed of sound.Considering the general formula 1 V ,๐ท ๐ถ๐ ๐ด ๐ V 2(2)๐ถ๐ฅ ๐ถ๐ ๐ถ๐ด ๐ตcontaining all parameters named above with(i) ๐ด: cross-section area of the projectile,(ii) ๐: air density,(iii) V: velocity of the projectile,(iv) ๐ถ๐ : air drag coefficient,(v) ๐ถ๐ด : environmental properties,(vi) ๐ต: ballistic coefficient,it is operative to find an appropriate approximation, so thatthe projectile can be specified. The parameters ๐ด, ๐, ๐ถ๐ , ๐ถ๐ด ,and ๐ต are unknown, whereas V can be defined precisely fromthe measured radar data.The air drag coefficient ๐ถ๐ for instance depends on thecritical velocity ratio, pictured in Figure 1. Since the dragcoefficient does not vary in a simple manner with Machnumber, this makes the analytic solutions inaccurate anddifficult to accomplish.One can see from this figure that there is no simpleanalytic solution to this variation. With computer powernowadays, we usually solve or approximate the exact solutions numerically, doing the quadratures by breaking the areaunder the curve into quadrilaterals and summing the areas. Ingeneral, there are three forms of the drag coefficient:(1) Constant ๐ถ๐ that is useful for the subsonic flightregime: ๐๐ 1

Mathematical Problems in Engineering3Let ๐ก denote the time, 0 ๐ก ๐ก๐ , with ๐ก 0 the initialtime and ๐ก ๐ก๐ the final time.The system of equations can be written asy 0โ๐๐ฅ ๐ข,๐๐กAltitude โmg โ 0jโkโiโ๐๐ฆ V,๐๐ก ๐๐ข ๐ถ๐ฅ V2 cos ๐,๐๐กxDistance(5)๐๐ค ๐ ๐ถ๐ฅ V2 sin ๐,๐๐กzwhereFigure 2: Mass point model with 3-DOF.V ๐ข2 ๐ค2(2) ๐ถ๐ inversely proportional to the Mach number that ischaracteristic of the high supersonic flight regime: inthis case, ๐๐ 1(3) ๐ถ๐ inversely proportional to the square root of theMach number that is useful in the low-supersonicflight regime: ๐๐ 1Carlucci and Jacobson [19] give a detailed description of theair drag coefficient.Another coefficient in common use in ballistics is theballistic coefficient ๐ต, which is defined as๐ต ๐,๐2(3)where ๐ and ๐ are the mass and diameter of the projectile[19]. Section 3.2 deals with the problem of estimating theunknown parameters.2.2. Equations of Motion. The aerodynamics and ballisticsliterature are quite diverse and terminology is far fromconsistent. This has particular significance in the coordinatesystems used to define the equations of motion. Nevertheless,this field of research has a long history and a lot of approaches.More details are discussed in [20โ24].In this paper, an Earth-bounded coordinate system isused. The Earth-bounded coordinate system {๐, ๐, ๐} is centered in the muzzle, with the axes ๐, ๐, ๐ pointing to fixeddirections in space. Axes ๐ is tangent to the Earth, ๐ is orthogonal to ๐ and runs against the gravity, and ๐ is orthogonal toboth ๐ and ๐, setting up a right-handed trihedron. The modelis illustrated in Figure 2.With the aforementioned parameters, the equilibrium offorces in this case can be described with the formula V ๐ ๐๐ ๐ท,๐๐ก(4)where ๐ is the total mass of the projectile.For setting up the system of equations, let (๐ฅ, ๐ฆ) denotethe projectile position and (๐ข, ๐ค) the velocity, with ๐ข determining the horizontal and ๐ค the vertical projection of thevelocity vector.(6)is the radial velocity and ๐ is the angle between the thrustvector and the ๐ฅ-axis: particularly๐ ๐๐ฆ.๐๐ฅ(7)3. ConceptThe purpose of the software is the calculation of trajectories.It receives the measured position of the projectile from thetracking radar and returns the predicted trajectory.A C code was written for the simulation and a GUI easesthe handling of the results. Radar data can be read in and willbe plotted for comparison.This chapter gives an overview of the methods used inthis paper. An integration method for differential equationsis introduced, which is used to solve the equations of motionin the previous section.3.1. Integration Method. There are several integration methods implemented, all providing better results compared to theanalytical methods used in [25].In this paper, the equations of motion are basically calculated with explicit, fixed step-size Runge-Kutta integrationtechniques. The advantage of this scheme over other schemesis that the approximating problems that result can be solvedvery efficiently and accurately. More details are discussed byRamezani [26].Knowing โ๐ ๐ก๐ 1 ๐ก๐ the algorithm can be programmedon the analogy of [27]๐ฅ๐ 1 ๐ฅ๐ 1(๐ก ๐ก ) (๐ 4 ๐3 ๐4 )6 ๐ 1 ๐ 1(8)with๐1 fl ๐ (๐ฅ๐ ) ,๐2 fl ๐ (๐ฅ๐ โ๐๐ ),2 1โ๐3 fl ๐ (๐ฅ๐ ๐ (๐1 ๐2 )) ,4๐4 fl ๐ (๐ฅ๐ โ๐ (๐2 2๐3 )) .(9)

4Mathematical Problems in EngineeringInitial values[a, b]c ๏ผ ๏ผญ(a b)Noc eTrajectory calculationwith a, bYesCx (a b)2Deviation calculationRadar dataOutput CxGold Section SearchNew interval a, bFigure 3: Programming flowchart.With a global discretization error ๐(โ4 ), the algorithm offersa tradeoff between high computing speed and best possibleresults [28].One may also select the Euler method in the program.Comparing to Runge-Kutta, the results are less precise dueto a lower order of consistency. Anyhow, the Euler methodachieves a significant improvement of computing time in themajority of cases with a global discretization error ๐(โ) [29].3.2. Iterative Optimization. In the mathematical model whichhas been described in Section 2.2, there are a number ofparameters missing. The other variables are given and canbe easily obtained through the measured trajectory elements. In order to determine the air drag ๐ท with the most accurateprecision, the following algorithm was developed.The air drag is chosen in a way so that the exterior ballisticmodel complies to the measured trajectory of the projectilein the best possible way. This implies that the sum of thedeviations between the calculated and the measured mortarpositions should be minimal:๐ min ๐ (๐ถ๐ฅ )๐222 min (๐ฅ๐๐ ๐ฅ๐๐ ) (๐ฆ๐๐ ๐ฆ๐๐ ) (๐ง๐๐ ๐ง๐๐ ) .(10)๐ 1The index ๐ refers to the coordinates which are measured bythe radar, while the index ๐ belongs to the coordinates whichare calculated by using numerical methods. The total amountof measurements is called ๐.Consequently, this is a nonlinear optimization. The objective function contains parameter ๐ถ๐ฅ . In order to find theoptimum, one of the fastest methods of one-dimensionaloptimization, the so-called โGolden Section Search,โ isapplied. It only needs one value of the objective functionfor each step of the calculation. The second value is takenfrom the preceding iteration step. This method possesses arobust and linear convergence speed to find the minimum of aunimodal continuous function over an interval without usingderivatives.The method chooses two points ๐ข1 ๐ข2 on the section[๐, ๐] considering Golden Section:๐ข1 ๐ ๐ข2 ๐ (๐ ๐) (3 5)2(๐ ๐) ( 5 1)2,(11).(12)If the inequality ๐(๐ข1 ) ๐(๐ข2 ) is complied, the minimum isin the interval [๐, ๐ข1 ]. In any other case, it will be found on thestretch [๐ข1 , ๐]. When this procedure is repeated, the intervalcan be shortened again. In case of a new partition [๐, ๐ข2 ],there are new boundaries ๐ข1 , ๐ข2 with ๐ข2 ๐ข1 . Therefore, onlytwo values of the goal functional are needed to be measuredduring the first step of the calculation [30].The goal is an optimal reduction factor for the searchinterval. Additionally, a minimal number of function calls arenecessary [31].Golden Section Search enables an iterative adjustment ofthe trajectory in each step by using the calculated parameter๐ถ๐ฅ for every previous iteration. Therefore, prediction getsmore precise in the course of time.The programming flowchart is illustrated in Figure 3.

Mathematical Problems in Engineering5TX-plotXY-plot80011700106009X (m) (103 )Y (m)500400300876200510045678X (m) (103 0.2Z (m) (103 )500Y (m)15T T (s)T (s)RadarNumericRadarNumericFigure 4: Forecast with the calculation period 3โ6 s.Table 1: Rocket Type 63 HE specification [17].Maximum rangeOverall lengthCaliberCross-sectional areaWeightLateral moment of inertiaLongitudinal moment of inertiaPosition of center of gravityStandard empty weightCombustion durationImpulseFlight time8.5 km839.0 mm107 mm7.72 cm218.84 kg0.98122 kgm20.03135 kgm2395.8 mm8.496 kg0.6 sec6.7 kNs21.5 sec4. Simulation ResultsAn example is calculated for a rocket Type 63 HE on acommon Intel x86. The data specification of the rocket islisted in Table 1.The trajectory was recorded by a Weibel radar of the typeMFDR-2100/35. It detects the RAM target at high accuracy. Itis designated to the RAM target with information receivedfrom a search radar. The accuracy is listed in Table 2. TheKalman filter illustrates the track error over time.Let ๐ก0 3 s be the time at which the radar detects thebullet. The final flight time is reached after ๐ก๐ 21.5 s.The duration of calculation is adjustable at will. Moretracking points will certainly help to get better results,but sometimes a fast interception of the RAM threat isindispensable. Starting the forecast with a 3-second period ofcalculation, there will be a mean square deviation of 566.9 mbetween the calculated and the real trajectory. By now itis possible to identify different RAM targets by regardingthe predicted trajectory characteristics. This example is illustrated in Figure 4. After 6 seconds of calculation, the meansquare deviation is reduced to 181.8 m. There are inaccuraciesin all axes of coordinates. The estimation of the calculatedparameter ๐ถ๐ฅ needs more iterative calculation steps at thispoint.Finally, after 12 seconds of calculation, the mean squaredeviation is reduced to 32.2 m and there is still enough

6Mathematical Problems in EngineeringTX-plotXY-plot80011700106009X (m) (103 )Y (m)500400300876200510045678X (m) (103 0.2Z (m) (103 )500Y (m)15T T (s)T (s)RadarNumericRadarNumericFigure 5: Forecast with the calculation period 3โ15 s.Table 2: Weibel radar accuracy [17].Time (ms)1020500Max. range (km)8.913.2Rg (m)0.200.0923.60.03Accuracy 2.0 kmAz (mills)El (mills)0.4910.4910.2200.220Kalman filter0.0690.069time for the command and control system to initiate allnecessary steps, for example, warning and defending. Theresults are shown in Figure 5. It is quite obvious that thesimulated altitude is overestimated. Mortar grenades have astrong change in altitude on their trajectory, a challenge forsimulation-based early prediction systems.The prediction of the trajectory allows the calculation ofthe point of impact. The future position of the projectile iscalculated through extrapolation of the measured values.It is clear that the prediction gets significantly better witheach iteration. Thus, certain areas in the field camp can bewarned partially and a counterattack can be initiated. TheRg (m)0.810.360.12Accuracy 4.0 kmAz (mills)1.9650.879El (mills)1.9650.8790.2780.278more the radar data available for the analysis, the closer theprediction to the measured trajectory. More tracking pointswill certainly help to get better results, but sometimes a fastinterception of the RAM threat is indispensable.With a prediction of 3 seconds into the future, forexample, which corresponds to an intercept range of almost3000 m, the computational error at the point of impact222๐๐ (๐ฅ๐๐ ๐ฅ๐๐ ) (๐ฆ๐๐ ๐ฆ๐๐ ) (๐ง๐๐ ๐ง๐๐ )(13)is smaller than 3 m. Here, the index ๐ refers to the coordinatesthat are measured and calculated at the point of impact.

Mathematical Problems in Engineering7Details and more examples are discussed by Ramezani et al.[10].[8]5. Summary and OutlookThis paper introduces an algorithm for early warning systemsused for command and control applications in out-of-areamissions and is based on the MONARC (modular navalartillery concept) project. The basic methods have been testedsuccessfully and they are used in fire guidance solutions forGerman frigates of type 124 and 125.The most important aspect is that one can distinguishbetween different projectiles in order to predict the trajectories and hit points more accurately. To calculate theirtrajectories, different flight phases are analyzed and thedesigns of the projectiles are estimated by the use of iterativeoptimization methods for approximating environmental andballistic properties.Future work concentrates on giving the user specificinformation of the projectile data. Further work has also tobe done on a 3-dimensional simulation.At the end, sophisticated simulation software will beestablished through which it will be possible to show andevaluate a real-time battlefield scenario.[9][10][11][12][13][14]Conflicts of InterestThe authors declare that they have no conflicts of interest.[15]References[16][1] M. Khalil, H. Abdalla, and O. Kamal, โTrajectory prediction fortypical fin stabilized artillery rocket,โ in Proceedings of the 13thInternational Conference on Aerospace Sciences and AviationTechnology, ASAT-13, 2009.[2] P. Chusilp, W. Charubhun, and N. Nutkumhang, โA comparative study on 6-DOF trajectory simulation of a short rangerocket using aerodynamic coefficients from experiments andmissile DATCOM,โ in Proceedings of the Second TSME International Conference on Mechanical Engineering, Krabi, Thailand,2011.[3] P. H. Zipfel, Modeling and Simulation of Aerospace VehicleDynamics, American Institute of Aeronautics and Astronautics,Reston, Va, USA, 2014.[4] S. An, K. B. Lee, and T. H. Kang, โFitting coefficient settingmethod for the modified point mass trajectory model usingCMA-ES,โ Journal of the Korea Institute of Military Science andTechnology, vol. 19, no. 1, pp. 95โ104, 2016.[5] P. Chusilp and W. Charubhun, โEstimation of impact pointsof an artillery rocket fitted with a non-standard fuze,โ inProceedings of the 2nd Asian Conference on Defence Technology(ACDT โ14), pp. 25โ31, 2014.[6] E. Scheuermann, M. Costello, S. Silton, and J. Sahu, โAerodynamic characterization of a microspoiler system for supersonicfinned projectiles,โ Journal of Spacecraft and Rockets, vol. 52, no.1, pp. 253โ263, 2015.[7] Y. Wang, W.-D. Song, D. Fang, and Q.-W. Guo, โGuidance andcontrol design for a class of spin-stabilized projectiles witha two-dimensional trajectory correction fuze,โ 26][27]Journal of Aerospace Engineering, vol. 2015, Article ID 908304,15 pages, 2015.C.-H. Lee and B.-E. Jun, โGuidance algorithm for projectilewith rotating canards via predictor-corrector approach,โ inProceedings of the 2014 IEEE Conference on Control Applications,CCA 2014, pp. 2072โ2077, October 2014.F. Fresconi, G. Cooper, and M. Costello, โPractical assessment ofreal-time impact point estimators for smart weapons,โ Journal ofAerospace Engineering, vol. 24, no. 1, pp. 1โ11, 2011.A. Ramezani, J. Cors, and H. Rothe, โComparison of methodsfor simulation-based early prediction of rocket, artillery andmortar trajectories,โ in Proceedings of the 2012 Autumn Simulation Multi-Conference (AutumnSim โ12), San Diego, Calif, USA,2012.B. Etkin, Dynamics of Atmospheric Flight, John Wiley and Sons,Hoboken, NJ, USA, 1972.O. Douglas and C. Mark, โModel predictive control of a directfire projectile equipped with canards,โ Journal of DynamicSystems, Measurement and Control, Transactions of the ASME,vol. 130, no. 6, pp. 0610101โ06101011, 2008.S. A. A. Ezeddine, Military Technical College, Cairo, Egypt,2009.E. Gagnon and M. Lauzon, โCourse correction fuze conceptanalysis for in-service 155 mm spin-stabilized gunnery projectiles,โ in Proceedings of the AIAA Guidance, Navigation andControl Conference and Exhibit, Honolulu, Hawaii, USA, August2008.S. Jankovic, J. Gallant, and E. Celens, โDispersion of an artilleryprojectile due to unbalance,โ in Proceedings of the 18th International Symposium on Ballistics, San Antonio, Tex, USA, 1999.M. S. Khalil, โTrajectory Predection of Flying Vehicle,โ Tech.Rep., Military Technical College, Cairo, Egypt, 2008.M. Knapp, P. Kossebau, A. Ramezani, and H. Rothe,Zuฬnderuntersuchung C-RAM, Bundesamt fuฬr Wehrtechnik undBeschaffung, Fachinformationsstelle BWB, Koblenz, Germany,2010.W. Wolff, Raketen und Raketenballistik, Elbe-Dnjepr-Verlag,Klitzschen, Germany, 2006.D. Carlucci and S. S. Jacobson, Ballistics: Theory and Design ofGuns and Ammunition, CRC Press, Boca Raton, Fla, USA, 2007.R. L. McCoy, Modern Exterior Ballistics, Schiffer MilitaryHistory, Atglen, Pa, USA, 1999.C. H. Murphy Ballistics Research Laboratory Report, AberdeenProving Ground, Md, USA, 1963.E. J. McShane, J. L. Kelley, and F. V. Reno, Exterior Ballistics,University of Denver Press, Denver, Colo, USA, 1953.J. D. Nicolaides, โOn the Free Flight Motion of Missiles HavingSlight Configurational Asymmetries,โ Tech. Rep., AberdeenProving Ground, Maryland, MD, USA, 1953.J. N. Nielsen, Missile Aerodynamics, American Institute ofAeronautics and Astronautics, Reston, VA, USA, 1988.I. Shaydurov and H. Rothe, Flugbahnvoraussage Moฬrsergranate, Helmut-Schmidt-University, Hamburg, Germany, 2008.A. Ramezani, Optimale Steuerung einer interplanetaren Flugbahn zum Mars [Diploma thesis], University of Bremen, TheCenter for Industrial Mathematics (ZeTeM), Bremen, 2010.W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery,Numerical Recipes 3rd Edition: The Art of Scientific Computing,Cambridge University Press, New York, NY, USA, 2007.

8[28] C. Buฬskens, Anleitungen zur Benutzung der Fortran-BibliothekNUDOCCCS, Westfaฬlische Wilhelms-University Muฬnster,1996.[29] W. Dahmen and A. Reusken, Numerik fuฬr Ingenieure undNaturwissenschaftler, Springer-Lehrbuch, Aachen, Germany,2008.[30] H. Rothe and S. Schroฬrder, Method for Determination of FireGuidance Solution, European Patent Office, Muฬnchen, Germany, 2006.[31] C. F. Gerald and P. O. Wheatley, Applied Numerical Analysis,Pearson, San Luis Obispo, Calif, USA, 2003.Mathematical Problems in Engineering

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ResearchArticle Simulation-Based Early Prediction of Rocket, Artillery, and Mortar Trajectories and Real-T