Description:
TECHNOLOGY AREA(S): Weapons
OBJECTIVE: To develop multi-source navigation algorithms to ensure weapons grade navigation capability for weapons systems in Anti-Access/Area Denial (A2AD) environments. This will address the need for Global Positioning System (GPS)-denied, A2AD over-land and/or over-water cooperative navigation capability applicable to low cost munitions.
DESCRIPTION: When access to GPS is denied, weapons can share relevant measurements and make inter-weapon measurements to provide improved mid-course navigation accuracy compared to single weapon inertial navigation system (INS) performance. Recent hardware advancements allow for accurate inter-agent range measurements; there is also potential for range rate, bearing, and bearing rate measurements. We seek a general decentralized navigation software framework capable of leveraging these and other measurements. The proposed solution should provide both an accurate local frame navigation solution (i.e. each agents’ position relative to its peers) and a reduction in global position uncertainty for the cooperating agents when compared to the single agent case. The cooperative navigation algorithm shall be implemented in a decentralized manner in the sense that it should not be expected that all sensor measurements are available to all agents at all times or even at a single centralized processor. If GPS or other georeferenced sources become available to any agents, the navigation algorithm should incorporate this information without requiring these sources to maintain a functional navigation solution. Preference will be given to proposals that are theoretically sound and approaches that are applicable to a wide range of vehicle and sensor types and performance characteristics. Approaches with more limited application will be considered but these limitations must be clearly defined. However, approaches that support heterogeneous groups of weapons are encouraged. Flexible estimation systems, ones that could be leveraged on a number of different platforms (with minimal modification), will be viewed favorably. Additionally, the estimation framework should also support graceful degradation of the cooperative INS solution to the single INS case. This effort should focus on navigation algorithm software development instead of hardware development. For proof-of-concept development and testing, inter-agent measurements that are computed from GPS and telemetry data may be used in place of actual measurements. However, any inter-agent measurements should be justified as feasible with additional hardware development. Communication data rates, robustness to intermittent or permanent loss of communication to one or more agents, and specific network connectivity requirements will also be taken into account. Proposals shall provide a representative concept of operations (CONOPS) appropriate for their proposed method along with the underlying system assumptions including sensors to be used and associated sensor qualities, frequency of any geo-registered data (i.e. GPS or registration of known features), number and trajectory of vehicles, and communication bandwidth required. The CONOPS and proposed technical work detailed in the proposal should be commensurate and the proposal shall provide anticipated navigation accuracy in both the global frame and relative frame (i.e. position of vehicles with respect to each other) for the associated CONOPS. For systems anticipating geo-referenced measurement inputs, the anticipated root-mean squared (RMS) global position error and 95th percentile error is appropriate (alternatively, the one and three sigma positioning uncertainty values). For systems with no geo-referenced feedback, or long time periods between geo-referenced feedback, the proposal should provide anticipated RMS (or one and three sigma) for positioning error as a function of time, or distance traveled, since last geo-update. Additionally, the anticipated RMS position error and 95th percentile error (or one and three sigma) for relative frame accuracy should also be included. The anticipated accuracies should be framed in terms of goal accuracies (what the program would aim to achieve) and required accuracies (accuracies which need to be met in order to claim program success) for the proposed CONOPS. It is understood that there are many trades within this research space, the proposal should be viewed as an opportunity to explain at least one CONOPS where the proposed solution is relevant and the expected performance this program would provide within that relevant environment. Finally, if the proposed development has anticipated non-military use cases, these should also be stated in the proposal.
PHASE I: Phase I should focus on navigation algorithm development with implementation in simulation. Software in-the-loop (SIL)/ hardware in-the-loop (HIL) or proof-of-concept hardware results are encouraged, but not required. The effort should clearly identify the effectiveness of the system, minimum sensor quality requirements (e.g. noise, resolution, etc.), communication requirements, and system limitations. No Gov’t materials, equipment data, or facilities will be used.
PHASE II: Phase II should focus on improvements to the navigation algorithm and real-time proof-of-concept hardware demonstrations and SIL/HIL testing as necessary. Plans for future partnering or internal development of inter-agent measurement hardware/software should be addressed, supporting transition potential for Phase III (planning done in Phase II).
PHASE III: The technology developed for this effort shall be demonstrated on weapons systems or appropriate surrogate systems (TRL 6/7) using sensor hardware capable of making the required inter-agent measurements or partner with a company that has an existing solution toward transitioning the technology to appropriate cooperative munition program(s).
REFERENCES:
1: Rajnikant Sharma and Clark Taylor. "Vision Based Distributed Cooperative Navigation for MAVs in GPS denied areas", AIAAInfotech@Aerospace Conference,Infotech@Aerospace Conferences, 2009. doi:10.2514/6.2009-1932.
2: V. Indelman, P. Gurfil, E. Rivlin and H. Rotstein, "Graph-based cooperative navigation using three-view constraints: Method validation," Position Location and Navigation Symposium (PLANS), 2012 IEEE/ION, Myrtle Beach, SC, 2012, pp. 769-776. doi: 10.1109/P
3: B. Kim et al., "Multiple relative pose graphs for robust cooperative mapping," Robotics and Automation (ICRA), 2010 IEEE International Conference on, Anchorage, AK, 2010, pp. 3185-3192. doi: 10.1109/ROBOT.2010.5509154.
4: J. Pentzer and E. Wolbrecht, "Improving autonomous underwater vehicle navigation using inter-vehicle ranging," Oceans, 2012, Hampton Roads, VA, 2012, pp. 1-8. doi: 10.1109/OCEANS.2012.6404994.
KEYWORDS: Multi-source Navigation Algorithms
