Keywords: 
• digital scene matching area correlation (DSMAC) /
• match probability /
• simulation model /
• route planning

Abstract: Digital scene matching area correlation (DSMAC) is a technique that has been proven to be highly successful as a navigational aid for autonomous,unmanned guided vehicles.In order to evaluate the scene correlation suitability or a performance of DSMAC algorithm,it is necessary to make a scene simulation model. Terrain contour matching (TERCOM) provides real-time fight control data and one dimensional height data for period near real-time position update of the vehicle's inertial navigation system (INS).Because the error of TERCOM is not sufficient to decide the area,the more exact two-dimensional navigation update technique DSMAC is used ^[1].It is well understood that the periodic update and the quantity of DSMAC navigation updates required is the function of:① the performance of gyro in the INS.② the flight time of mission,and ③ the precision with which the unmanned vehicle must overfly a reconnaissance point or target location.However,less understood are the processes by which the scene correlation effectiveness of a candidate point can be predicted and ranked using a multi-parameters figure-of-merit (FOM) and how the selection of an individual FOM and the resulting accumulated series of scene suitability FOMS can be related to all mission reliability. Computer models currently available to predict DSMAC scene suitability use a single parameter ranking system,such as signal-to-noise (S/N) ratio.Current models also assume the aircraft flies straight and level,and the optimum heading,while over the scene reference area.These limitations require the introduction of an adaptive flight path modification capability in future robotic aircraft,which provides the ability for defense avoidance,or inflight re-routing.This capability will certainly require a more robust DSMAC scene selection process that is able to accommodate variations in aircraft altitude,attitude,orientation and initial position uncertainty relative to the potential scene.Current model is not enough to evaluate a real vehicle. The subject of this paper is the development of a Monto-Carlo simulation technique capable of modeling a robust DSMAC selection process,as discussed above,which characterizes scene suitability using a multi-parameter FOM.The Monte-Carlo simulation described in this paper is modular and expandable to support future studies involving other altitude reference baseline (e.g.global positioning system),other height finding instrument (e.g.LASER altimeters),and other map reference derivatives (e.g.interferometric SAR maps). In this paper,we propose a DSMAC simulation model.A Monte-Carlo simulation is produced to evaluate the potential DSMAC success rate under various scenarios and correlation algorithm.The simulation details are provided together with some preliminary result to demonstrate the feasibility of the proposed technique.It has been shown that the proposed technique can provide a cost-effective enhancement to the TAN-based mission planning process.For the future work,it can be transplanted to parallel process.It can improve the speed of calculation evidently.