Abstract:
A method of determining survivability is disclosed. The method can include selecting a mission scenario and providing data associated with the scenario as input to a plurality of low-level modeling tools each associated with a corresponding spectrum, and performing a spectral analysis of the selected scenario using each of the low-level modeling tools for the corresponding spectrum. The method can also include generating an event probability matrix for each analyzed spectrum based on the output of the low-level model, the event probability matrix including a probability of detection, a probability of tracking, and a probability of engagement for each of a plurality of mission scenario reference points. Using the event probability matrix as input, a constructive analysis can be performed using a high-level simulation system configured to simulate actual event occurrence for a specific run of the mission scenario and a probability of survival based on a result of the constructive analysis can be determined. A report of the probability of survival, as well as other statistics relevant to operational performance and/or survivability can be provided as output.

Description:
Embodiments of the present invention relate generally to determining survivability, and in particular to modeling mission survivability. 
     Military aircraft and rotorcraft face an increasingly lethal and proliferated multi-spectral threat from weapon mounted sensors. A need may exist to consider these weapons and their various capabilities at a design, engineering, or operational planning stage of a military aircraft or rotorcraft. 
     Embodiments of the present invention may provide a capability for analysis of survivability subsystem design and concept of operation (CONOPS) effectiveness. This can allow a quantitative comparison of overall platform design and recommended usage. Also, design validation and requirements verification of survivability subsystems typically requires a detailed understanding of specific aircraft mission operations. Costly post-development correction may be needed if an operational analysis is not performed at the outset of a system design or engineering effort. The operational analysis can provide a cost-effective approach to understanding survivability subsystem deign effectiveness in operational environments. Additionally, the cost and effectiveness of various design alternatives can be more easily compared using an operational analysis. 
     In general, embodiments of the present invention can use one or more high fidelity modeling tools to evaluate aircraft mission level survivability system performance. An event probability interface, including engagement/kill probabilities for one or more threats, can be used in a simulation (e.g., a monte carlo simulation) to simulate aircraft survivability through a number of specific missions. By running a statistically significant number of trials, overall probability of mission survival can be evaluated. In addition to providing a tool for survivability subsystem design and engineering efforts, the embodiments can be used to evaluate tactics, techniques, and procedures (TTPs) in order to find the most effective (i.e., survivable) way of flying a mission in a threat environment. 
     Thus, embodiments of the present invention can provide for a system level survivability performance analysis to be performed using results from one or more high-fidelity modeling tools. The resulting method, system or software can be used to evaluate mission-level performance and compare subsystem design issues. The methods, system, and software can provide a survivability modeling and simulation infrastructure that can be used in various aircraft and rotorcraft design and engineering programs. The survivability modeling methods, system and software can be used to demonstrate concepts, validate and shorten design cycles, and provide a cost-effective alternative to verification testing for subsystems, such as survivability subsystems. 
     While aircraft and rotorcraft are used as examples in this application for illustration purposes, it should be appreciated that the methods, systems and software of various embodiments can be used with military vehicles, spacecraft, commercial vehicles, private vehicles, unmanned aircraft and vehicles, autonomous machines or vehicles, and/or any type of machine or vehicle where a determination of survivability may be useful or desired. Vehicles, as used herein, is intended to refer to any type of transportation apparatus including, but not limited to, airplanes, helicopters, rockets, missiles, gliders, lighter-than-air craft, unmanned aerial vehicles (UAVs), cars, trucks, motorcycles, tanks, military ground transports, heavy equipment, naval vessels, watercraft, submarines, hover craft, human powered vehicles, and/or the like. 
     One exemplary embodiment can include a method of determining survivability. The method can include selecting a mission scenario and providing data associated with the scenario as input to a plurality of low-level modeling tools each associated with a corresponding spectrum, and performing a spectral analysis of the selected scenario using each of the low-level modeling tools and a low-level model for the corresponding spectrum. The method can also include generating an event probability matrix for each analyzed spectrum based on the output of the low-level model, the event probability matrix including a probability of detection, a probability of tracking, and a probability of engagement for each of a plurality of mission scenario reference points. Using the event probability matrix as input, a constructive analysis can be performed using a high-level simulation system configured to simulate actual event occurrence for a specific run of the mission scenario and a probability of survival based on a result of the constructive analysis can be determined. A report of the probability of survival can be provided as output. 
     Another exemplary embodiment can include a computer program product including a computer readable medium encoded with software instructions. When the software instructions are executed by a computer, they cause the computer to perform predetermined operations. The predetermined operations including the steps of selecting a mission scenario and providing data associated with the scenario as input to a low-level modeling tool associated with a corresponding spectrum; and performing a spectral analysis of the selected scenario using the low-level modeling tool and a low-level model for the corresponding spectrum. The steps can also include generating an event probability matrix for the analyzed spectrum based on the output of the low-level model, the event probability matrix including a probability of detection, a probability of tracking, and a probability of engagement for each of a plurality of mission scenario reference points. The steps can include performing a constructive analysis by providing the event probability matrix as input to a high-level simulation system configured to simulate actual event occurrence for a specific run of the mission scenario. The steps can include determining a probability of survival based on a result of the constructive analysis; and providing a report of the probability of survival as output. 
     Another exemplary embodiment can include a computer system for determining survivability. The computer system includes a processor and a memory including software instructions that are adapted to cause the computer system to perform a series of steps. The steps include selecting a mission scenario and providing data associated with the scenario as input to a low-level modeling tool associated with a corresponding spectrum, and performing a spectral analysis of the selected scenario using the low-level modeling tool and a low-level model for the corresponding spectrum. The steps can also include generating an event probability and performing a constructive analysis by providing the event probability matrix as input to a high-level simulation system configured to simulate actual event occurrence for a specific run of the mission scenario. The steps can include determining a probability of survival based on a result of the constructive analysis, and providing a report of the probability of survival as output. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Exemplary embodiments of the present invention will be described with reference to the accompanying drawings, wherein: 
         FIG. 1  is a block diagram of an exemplary system for modeling mission survivability; 
         FIG. 2  is a flowchart of an exemplary method for modeling mission survivability; 
         FIG. 3  is a block diagram of an exemplary process for modeling mission survivability including a plurality of low-level models; 
         FIG. 4  is a bock diagram showing inputs to an exemplary constructive analysis; 
         FIG. 5  is a block diagram showing inputs to exemplary low level models; and 
         FIG. 6  is a block diagram showing output results from an exemplary constructive analysis. 
     
    
    
     DETAILED DESCRIPTION 
       FIG. 1  is a block diagram of an exemplary system for modeling mission survivability. In particular, a mission survivability modeling system  100  receives input data  102  and outputs a report  104  including a probability of survival. The mission survivability modeling system includes a low-level model  106 , an event probability interface  108 , and a constructive analysis module  110 . 
     In operation, the system  100  receives input  102 . The input  102  can include platform, threat, and/or environment data. Using the input  102 , the system  100  can use a low-level model  106  to model mission survivability for a particular threat type. The low-level model can be a verified, validated and accredited modeling tool for a particular type of sensor technology, for example, radar or infrared. This allows for a detailed simulation of a mission scenario for a given threat type and/or sensor technology. 
     The low-level model  106  can produce an event probability interface  108  that represents one or more probabilities for each of a plurality of intervals distributed along the course of the mission. The intervals can be based on distance, time, position, and/or a combination of the above. 
     The event probability interface  108  can include probabilities of detection (P D ), tracking (P T ), and engagement (P E ). The event probability interface can include a distribution of engagement (D E ) for each interval. The event probability interface can also include a probability of a hit given a weapon fire (P H/S ) and a probability of a kill given a hit (P K/H ). All of the above probabilities can be based on an aspect (i.e., an orientation) of the aircraft being simulated, geometry of the engagement, a position of a threat, a capability of the aircraft being analyzed, and a capability of the threat. 
     For example, the probability event interface can include a probability of engagement for each interval on the mission scenario. The P E  for each interval can be determined based on the aspect of the aircraft, the location of the threat, and the capability of the threat. 
     The event probability interface  108  is provided as input to a constructive analysis module  110 . The constructive analysis module can be a module of an integrated program for mission survivability modeling or can be a standalone application such as a simulation software tool. The constructive analysis module  110  can determine a contribution of danger of each type of threat for an entire mission. By using highly detailed information for a threat type from the low-level model  106 , the constructive analysis module is able to provide a probability of survival that incorporates the accuracy of the low-level model  106  for a particular threat type. 
     The constructive analysis module  110  produces an output report  104  that can include a probability of survival. The report  104  can be provided in any of a variety of forms including printed, shown on a video display, as audio, as an entry in database, as an electronic communication, and/or the like. The particular method of providing the report  104  can depend on the contemplated use of the embodiment. 
     The report  104  can be used to evaluate mission performance and inform subsystem design choices. The report  104  can also be used for mission planning purposes. The report  104  can include an overall probability of survival and/or a probability of survival for each of the intervals of the mission. By representing probabilities distributed over intervals of a mission, the system can determine, for example, at which points in a mission an aircraft is most vulnerable and from what type of threat. This information can be used in a design activity, for example to alter a design of a survivability system to better protect the aircraft, or a mission planning activity, for example changing a recommended flight aspect at a certain interval of the mission based on an indicated probability of survival for that interval. 
     Trade studies can be performed using the system  100 . For example, a mission scenario can be simulated in which a first scenario includes an aircraft equipped with “Subsystem A” and a second scenario includes an aircraft equipped with “Subsystem B.” By using the system  100  to output a survivability report  104  based on each of the scenarios, the effectiveness of Subsystems A and B can be compared and a design choice can be made using the comparison result. In another example, a mission scenario survivability simulation can be performed with an aircraft being equipped with a particular subsystem, and another mission scenario survivability simulation can be performed with the aircraft not being equipped with the particular subsystem. The results of these simulations can be used tom compare the effectiveness of the particular subsystem. 
     It should be appreciated that system  100  can be comprised of computer software, electronic and/or computer hardware, or a combination of the above. 
       FIG. 2  is a flowchart of an exemplary method for modeling mission survivability. The method begins at step  202  and continues to step  204 . 
     In step  204 , platform, threat, and/or environmental data can be provided. The method continues to step  206 . 
     In step  206 , a low-level simulation or modeling can be performed using a low-level modeling tool that may be adapted for a specific threat and/or sensor technology type. Control then continues to step  208 . 
     In step  208 , scenario-dependent event probabilities can be generated by the low-level modeling tool. These event probabilities can be output using the event probability interface described above and below. Control then continues to step  210 . 
     In step  210 , a high-level simulation can be performed. Inputs to the high-level simulation can include any event probability interfaces produced by the low-level modeling tool. Inputs can also include some or all of the data provided to the low-level modeling tool, such as platform, threat, environment, mission information, and/or the like. Control continues to step  212 . 
     In step  212 , an output report can be generated that can include a probability of survival for the mission. The output report can also include other information as described below in reference to  FIG. 6 . Control then continues, optionally to step  214  or, if not to step  214  then to step  216  where the method ends. 
     In optional step  214 , one or more parameters of a scenario or mission can be changed and the low-level and high-level simulations performed again. The changed parameters can relate to any aspect of the mission including, but not limited to, tactics, aircraft design (or platform configuration), threat capability, threat location, mission route, or the like. Performing a simulation with different parameters can provide an ability to compare survivability outcomes using different mission parameters. 
       FIG. 3  is a block diagram of an exemplary process for modeling mission survivability including a plurality of low-level models. In particular, platform, threat, and/or environment data  302  can be provided. The data  302  can be used as input to a plurality of low-level modeling tools. The low-level modeling tools can include, for example, infrared (IR)  304 , radio frequency (RF)  306 , visual  308 , acoustic  310 , or other  312  type of low-level model now in use or later-conceived. The low-level models can be selected based on a contemplated mission or scenario, the types of threats that may be encountered, and the platform that may be used for the mission. It should be appreciated that the low-level modeling tools  304 - 312  shown in  FIG. 3  are for illustration purposes and more or less low-level modeling tools of the same or different type can be used with the embodiment. Further, the embodiment may be used with low-level modeling tools for existing technologies or threats and may also be used with low-level modeling tools developed for future technologies or threats not presently known. 
     The low-level modeling tools  304 - 312  can provide a detailed analysis of a portion or all of a mission or scenario. The detailed analysis can include an assessment of various probabilities at each interval along the mission. The intervals may be predetermined or determined dynamically based on mission or scenario parameters. 
     The results of the low-level modeling tools  304 - 312  can be output as a set of event probabilities in an event probability interface. These event probability interfaces can be used as input to a constructive analysis tool  314  (e.g., a simulation tool such as Satellite Tool Kit® sold by Analytical Graphics, Inc. of Exton, Pa.). 
     The constructive analysis tool  314  can use the event probability interfaces to generate a report  316  that can include an overall probability of survival for the mission based on each of the low-level modeling tools. 
       FIG. 4  is a bock diagram showing inputs to an exemplary constructive analysis. In particular, a constructive analysis module  402  can receive input from a number of sources. These sources can include low-level modeling tools, interface definitions, and other parameters. The parameters  404  can include, for example, random seed creation parameters, event probability selection logic, event definitions, scenario run logic, and/or the like. The interface definitions can include an event probability interface  406 . The low-leveling modeling tools can include RF models  408  and  410 , IR models  412  and  414 , a visual model  416 , an actual or real data model  418  and an acoustic model  420 . 
     In operation, the low-level modeling tools  408 - 420  can output data in the same or different formats. The output data can be provided or conformed to the event probability interface  406 . The event probability interface  406  can be an interface definition usable by the constructive analysis module  402  and the low-level models  408 - 420 . The interface and data can be in a text format, binary format, or other format, such as extensible markup language (XML). In general, any computer readable format may be used for the event probability interface  406  and data provided by the low-level models  408 - 420 . 
     Using the above inputs, the constructive analysis module  402  can perform a high level mission survivability simulation and output a report of the results of the simulation. The constructive analysis module  402  can be a stand alone program or a program integrated with the low-level models. 
       FIG. 5  is a block diagram showing inputs to exemplary low level models. The low-level models may require various input data in order to perform the low-level analysis of a mission or scenario. This input data can include air vehicle (or other type of vehicle or craft) performance data  502 , environment data  504 , terrain data  506 , platform signature data  508 , threat weapons data  510 , threat performance data  512 , platform countermeasure data  514 , and/or the like. 
     In operation, the inputs  502 - 514  can be provided to one or more low-level models  516 . Each of the low-level models can then produce an event probability matrix, or event probability interface  518 . As mentioned above, these event probability interfaces can be provided to a high-level or constructive analysis, module for performing a survivability modeling, analysis or simulation of some or all of a mission or scenario. 
       FIG. 6  is a block diagram showing output results from an exemplary constructive analysis. In particular, an event probability matrix, or event probability interface,  602  can be provided to a constructive analysis module  604 . The constructive analysis module can perform a high-level simulation using the low-level event probability interface inputs and produce an output report. The output report can list a probability of survival  608  for some or all of a mission or scenario. The output report can also include other information  606  that may have factored into the probability of survival. The other information  606  can include an average detection range, an average tracking range, an average lock-on range, an average engagement range, an average time-to-engagement range, and/or the like. 
     It should be appreciated that any steps described above may be repeated in whole or in part in order to perform a contemplated mission survivability modeling task. Further, it should be appreciated that the steps mentioned above may be performed on a single or distributed processor. Also, the processes, modules, and units described in the various figures of the embodiments above may be distributed across multiple computers or systems or may be co-located in a single processor or system. 
     Embodiments of the method, system and computer program product for modeling mission survivability, may be implemented on a general-purpose computer, a special-purpose computer, a programmed microprocessor or microcontroller and peripheral integrated circuit element, an ASIC or other integrated circuit, a digital signal processor, a hardwired electronic or logic circuit such as a discrete element circuit, a programmed logic device such as a PLD, PLA, FPGA, PAL, or the like. In general, any process capable of implementing the functions or steps described herein can be used to implement embodiments of the method, system, or computer program product for modeling mission survivability. 
     Furthermore, embodiments of the disclosed method, system, and computer program product for modeling mission survivability may be readily implemented, fully or partially, in software using, for example, object or object-oriented software development environments that provide portable source code that can be used on a variety of computer platforms. Alternatively, embodiments of the disclosed method, system, and computer program product for modeling mission survivability can be implemented partially or fully in hardware using, for example, standard logic circuits or a VLSI design. Other hardware or software can be used to implement embodiments depending on the speed and/or efficiency requirements of the systems, the particular function, and/or a particular software or hardware system, microprocessor, or microcomputer system being utilized. Embodiments of the method, system, and computer program product for modeling mission survivability can be implemented in hardware and/or software using any known or later developed systems or structures, devices and/or software by those of ordinary skill in the applicable art from the functional description provided herein and with a general basic knowledge of the computer and/or simulation arts. 
     Moreover, embodiments of the disclosed method, system, and computer program product for modeling mission survivability can be implemented in software executed on a programmed general-purpose computer, a special purpose computer, a microprocessor, or the like. Also, the modeling mission survivability method of this invention can be implemented as a program embedded on a personal computer such as a JAVA® or CGI script, as a resource residing on a server or graphics workstation, as a routine embedded in a dedicated processing system, or the like. The method and system can also be implemented by physically incorporating the method for modeling mission survivability into a software and/or hardware system. 
     It is, therefore, apparent that there is provided in accordance with the present invention, a method, system, and computer program product for modeling mission survivability. While this invention has been described in conjunction with a number of embodiments, it is evident that many alternatives, modifications and variations would be or are apparent to those of ordinary skill in the applicable arts. Accordingly, applicants intend to embrace all such alternatives, modifications, equivalents and variations that are within the spirit and scope of this invention.