Real-time battle management is focused on the real-time analysis of a missile threat and the optimized allocation of missile defense resources to engage and defeat the threat. It requires a dynamic, adaptive system that integrates multiple and diverse sensor, weapon, communications and control systems to coordinate a distributed engagement solution.
Real-time battle management is a multi-faceted problem that requires the integration of many diverse analysis tools:
- Sensor integration
- Track correlation
- Threat analysis (projected impact location, potential damage scoring)
- Probability of engagement success analysis (analysis of engagement options, battlespace, probability of kill)
- Constrained weapon resource allocation
- Constrained sensor resource allocation
- Integrated sensor-weapon management
- Optimization according to mission objectives
- Dynamic adaptation of tasking plans to adjust to changing threat environment
- Distributed and global battle management
- Wide bandwith, high quality of service communication networks
- Distributed and parallelizable computational frameworks
The solutions to the real-time battle management problem require several complex and interacting algorithmic tools to develop an effective, integrated solution. TechFinity has developed advanced algorithmic solutions to address some of these key problem areas, including the following:
- Probabilistic Threat and Engagement Analysis
- Optimized Sensor Resource Management
- Optimized Weapon Resource Management
- Joint Sensor-Weapon Management
- Distributed Battle Management
In summary, the key benefits of the TechFinity algorithmic approaches for real-time battle management are summarized as follows:
- Probabilistic algorithmic approaches have been developed for the major analysis components of real-time battle management to ensure unbiased estimates are generated for critical analyses
- Fast numerical methods have been developed to support real-time computation of analysis and optimization algorithms
- Supports optimization of sensor and weapon resource tasking, while ensuring that the joint sensor-weapon engagement plans meet mission level objectives
- Scalable, parallelizable algorithms provide the robust support needed to handle large raid scenarios.
Probabilistic Threat Analysis
The determination of threat value and the potential damage to defended assets is evaluated using probabilistic threat analysis algorithms. TechFinity’s algorithms address the uncertainty of intended targets by evaluating the potential damage by a given threat within impact ellipses derived from the threat’s track covariance. Fast numerical methods support scalability of threat analyses to large raid sizes while still providing real-time performance. Methods also support treatment of defended assets as either point assets or area assets for improved modeling of threat values and potential damage.
Probabilistic Engagement Analysis
The single shot probability of kill associated with a given threat-interceptor pair is calculated by the probabilistic engagement analysis algorithms. TechFinity’s algorithmic approach provides interceptor specific models that capture a number of interceptor-specific characteristics and constraints that affect both the battlespace of feasible engagements and the expected performance of intercepts within the feasible engagement windows. Fast numerical methods have been developed to compute an un-biased single shot probability of kill, along with corresponding covariance measures that assess the intercept performance characteristics while accounting for predicted threat state uncertainties and interceptor constraints.
Optimized Sensor Resource Management
The overall performance of the sensor enterprise can be optimized using sensor resource management algorithms that seek to optimize coverage and resource utilization of the sensors in the network. TechFinity’s algorithms support an adaptive, dynamic assessment of current and future sensor requirements based on projected threat trajectories and planned engagements. The optimization techniques can quickly identify sensor tasking adjustments that can be recommended to individual sensor elements by the battle manager to best optimize use of resources to achieve mission performance objectives. These tasking adjustments can schedule key sensor tasks such as search, track, discrimination, interceptor support, and kill assessment while minimizing the overloading of sensors and maximizing fields of view on individual threat objects.
Optimized Weapon Resource Management
Mission objectives are the key drivers in optimizing weapon resource management. TechFinity’s algorithms provide probabilistic methods that support both threat-based and asset-based mission objectives, while accounting for a variety of constraints, including weapon inventories, threat forecasting and inventory preservation, and overall mission performance. The adaptive, dynamic engagement planning algorithms seek weapon tasking plans that optimize overall system performance rather than looking only at the performance of individual threat-shooter pairings. Several optimization methods have been developed, which are scalable through parallelizable methods to support large raid sizes.
Joint Sensor-Weapon Management
The integration of sensor and weapon management is a natural extension of the optimized sensor and weapon resource management algorithms. The existing engagement planning algorithms are extended to include assignment of both a sensor and weapon to a threat, and selecting engagement plans that where sensor support is available to support all required aspects of the engagement. The tasking of sensors is on a per threat / per task basis so that advanced engagement planning techniques such as launch on remote or engage on remote can be handled by the system.
Distributed Battle Management
The coordination of the battle management activities across multiple regions is an increasingly important capability in missile defense in order to address the potential for coordinated simultaneous attacks in different regions or theaters. TechFinity is developing distributed battle management techniques that will allow multiple battle manager nodes, each with their own resources and areas of responsibility, to perform a coordinated engagement planning effort that will support global optimization of regional efforts.