Release Date
November 29th, 2023
Open Date
January 3rd, 2024
Due Date(s)
February 21st, 2024
Close Date
February 21st, 2024
Topic No.


Weapons Scheduling for Uncertain Weapon-Target Assignment


Department of DefenseN/A


Type: SBIRPhase: BOTHYear: 2024


The Department of Defense (DOD) is seeking proposals for a Small Business Innovation Research (SBIR) program with a focus on the topic of "Weapons Scheduling for Uncertain Weapon-Target Assignment". The research aims to develop an automated capability for the Ship Self-Defense System (SSDS) that maximizes weapon scheduling effectiveness in scenarios where explicit weapon-target assignment solutions are not possible. The technology should generate engagement schedules enabling incoming target raid annihilation in the face of uncertainty regarding the number of inbound targets, their physical location, and other characteristics. The proposed solutions should be compatible with the SSDS combat management system (CMS) and use common data, but not depend on integrating new weapons or sensors. The research should be explainable and demonstrated through low- to medium-fidelity modeling and simulation approaches. The project will have a Phase I and Phase II, with the potential for classified work in Phase II. The technology developed should have dual-use applications, including commercial resource management and scheduling challenges. The deadline for proposals is February 21, 2024. For more information, visit the SBIR topic link or the solicitation agency website.


OUSD (R&E) CRITICAL TECHNOLOGY AREA(S): Advanced Computing and Software


The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with the Announcement. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws.


OBJECTIVE: Develop an automated capability for the Ship Self-Defense System (SSDS) that maximizes weapon scheduling effectiveness where explicit weapon-target assignment solutions are not possible.


DESCRIPTION: Current US Naval platforms use a variety of onboard sensors, communications networks, data processing systems, weapons, and other components organized into a combat system to detect, track, and classify inbound targets, determine how to best employ weapons and countermeasures to defeat those targets, and then use those weapons and countermeasures to maximum effect. This involves explicit selection, scheduling, and assignment of self-defense weapons to inbound targets to achieve an optimal defensive solution, often across multiple layers of weapons in range (i.e., “depth of fire”). This process uses a variety of factors to make explicit weapon-target assignments (WTA) and schedule engagements against incoming targets, including but not limited to: assessments of target attributes, the number of detected targets, the number of defensive weapons in inventory, doctrine describing how and when particular weapons are used, and other factors. Furthermore, engagement schedules are “dynamic, changing as new sensor data are provided, additional targets are disclosed, and initially scheduled engagements are executed” [Ref 1]. This is a challenging and complex process.

Due to the ever-shifting landscape posed by our adversaries, future Naval combat systems must be resilient to scenarios in which generating engagement schedules with explicit WTA approaches are not tenable and no current solution is available. The Navy therefore seeks an automated capability that generates engagement schedules enabling incoming target raid annihilation in the face of uncertainty regarding the number of inbound targets, the physical location and position of targets, knowledge of expected inbound target behavior during terminal homing phases, inferred target identity, and other characteristics occurring during off-axis, massed and/or swarm attacks [Refs 2, 3]. Proposals using machine learning approaches will also be considered, but candidate solutions must be capable of generating schedules against completely novel, never-before-seen threats and raid conditions, and in scenarios for which training data for use in ML-focused solutions cannot be provided. Solutions must reside inside and support integration into the SSDS combat management system (CMS) (that is, algorithms should not be targeted for integration into weapons or sensors), but must use data (e.g., radar track and state data, sensor data, and others) that are common to other CMSs. Furthermore, the solution should consider the potential complexities introduced by distinctions between CMS-provided WTA, and WTA approaches decided by defensive interceptors themselves as they near their targets [Ref 4]. Finally, the solution must be compatible with current combat system operational characteristics and constituent components (that is, solutions cannot depend on integrating new weapons and/or sensors into the combat system) [Ref 1]. The solution used to demonstrate proposed methods and/or algorithms for scheduling under WTA uncertainty should be demonstrated under low- to medium-fidelity modeling and simulation approaches. Simulation and analysis results should be presented in the form of scenario descriptions, Red and Blue force asset laydown(s), and engagement timelines using synthetic yet realistic engagement events, parameters, and data. The inner workings of proposed algorithmic approaches must be explainable.

Three SSDS Top Level Requirements (TLRs) would be supported by this investigation. These TLRs will be provided by the government to the awardee. These requirements are:

• The SSDS CS shall determine, recommend and apply weapons tactics to include firing policy, salvo size, and salvo spacing [SSDS_CS_TLR-1571];

• The SSDS CS shall reevaluate and rebuild HK and SK schedules periodically, as well as when certain events occur that can change target and resource status [SSDS_CS_TLR-1674]; and

• The SSDS CS shall consider the effects of multiple targets in the weapon's field of view on weapon performance when building the engagement schedule [SSDS_CS_TLR-1684].


Work produced in Phase II may become classified. Note: The prospective contractor(s) must be U.S. owned and operated with no foreign influence as defined by 32 U.S.C. § 2004.20 et seq., National Industrial Security Program Executive Agent and Operating Manual, unless acceptable mitigating procedures can and have been implemented and approved by the Defense Counterintelligence and Security Agency (DCSA) formerly Defense Security Service (DSS). The selected contractor must be able to acquire and maintain a secret level facility and Personnel Security Clearances. This will allow contractor personnel to perform on advanced phases of this project as set forth by DCSA and NAVSEA in order to gain access to classified information pertaining to the national defense of the United States and its allies; this will be an inherent requirement. The selected company will be required to safeguard classified material during the advanced phases of this contract IAW the National Industrial Security Program Operating Manual (NISPOM), which can be found at Title 32, Part 2004.20 of the Code of Federal Regulations. Reference: National Industrial Security Program Executive Agent and Operating Manual (NISP), 32 U.S.C. § 2004.20 et seq. (1993).


PHASE I: Develop a concept for a capability to generate SSDS engagement schedules that enables incoming target raid annihilation without using explicit weapon-target assignment approaches. Demonstrate the feasibility of the concept to meet the conditions outlined in the Description section through modeling, simulation, and analysis. The Phase I Option, if exercised, will include the initial design specifications and capabilities description to build a prototype solution in Phase II.


PHASE II: Develop and deliver an engagement scheduling system prototype capable of meeting realistic engagement and operational requirements based on the results of Phase I. Demonstrate at a Government- or company-provided facility that the prototype meets all parameters detailed in the Description. The technology will be assessed by Navy subject matter experts.


It is probable that the work under this effort will be classified under Phase II (see Description section for details).


PHASE III DUAL USE APPLICATIONS: Support the Navy in transitioning the technology to Navy use. The technology will go through system integration and qualification testing for the prototype engagement scheduling approach developed in Phase II. This prototype will be delivered to support the Navy through a critical experiment conducted jointly by the awardee and combat system engineering agent (CSEA). This is expected to take place in a live environment with tactical SSDS CMS software. Integrate the prototype into the SSDS CMS.

Dual use applications to consider include commercial resource management, delivery, and scheduling challenges that are particularly vulnerable to uncertainty that is difficult to deterministically quantify and/or changes over time.



Bath, W. G. “Overview of Platforms and Combat Systems.” Johns Hopkins APL Technical Digest, Volume 35, Number 2, 2020.
Kline, A.; Ahner, D. and Hill, R. “The Weapon-Target Assignment Problem.” Computers and Operations Research, Volume 105, 2019.
Ahmadi, M.; Ono, M.; Ingraham, M.; Murray, R. and Ames, A. “Risk-averse Planning Under Uncertainty.” 2020 American Control Conference.
Shumalov, V. and Shima, T. “Weapon-Target Allocation Strategies in Multiagent Target-Missile-Defender Engagement.” Journal of Guidance, Control, and Dynamics, 40(10), pp. 2452-2464.


KEYWORDS: Operational characteristics; WTA uncertainty; weapon-target assignment; schedule optimization; stochastic optimization; weapons and countermeasures