human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "velocity position integration formula part i application to in flight coarse alignment"
  Abstract: The in-flight alignment is a critical stage for airborne inertial navigation system/Global Positioning System (INS/GPS) applications. The alignment task is usually carried out by the Kalman filtering technique that necessitates a good initial attitude to obtain a satisfying performance. Due to the airborne dynamics, the in-flight alignment is much more difficult than the alignment on the ground. An optimization-based coarse alignment approach that uses GPS position/velocity as input, founded on the newly-derived velocity/position integration formulae is proposed. Simulation and flight test results show that, with the GPS lever arm well handled, it is potentially able to yield the initial heading up to 1 deg accuracy in 10 s. It can serve as a nice coarse in-flight alignment without any prior attitude information for the subsequent fine Kalman alignment. The approach can also be applied to other applications that require aligning the INS on the run.

Connected through hyperedge HE-1 (induced by source paper "on inertial navigation and attitude initialization in polar areas"):
  with members:
    - "a new technique for ins gnss attitude and parameter estimation using online optimization"

Connected through hyperedge HE-2 (induced by source paper "semi analytic method for sins attitude and parameters online estimation"):
  with members:
    - "optimization based alignment for strapdown inertial navigation system comparison and extension"
    - "a new technique for ins gnss attitude and parameter estimation using online optimization"

Connected through hyperedge HE-3 (induced by source paper "optimization based alignment for strapdown inertial navigation system comparison and extension"):
  with members:
    - "a new technique for ins gnss attitude and parameter estimation using online optimization"
    - "velocity position integration formula part ii application to strapdown inertial navigation computation"
    - "observability of strapdown ins alignment a global perspective"

Connected through hyperedge HE-4 (induced by source paper "underwater doppler navigation with self calibration"):
  with members:
    - "a new technique for ins gnss attitude and parameter estimation using online optimization"
    - "velocity position integration formula part ii application to strapdown inertial navigation computation"
    - "observability of strapdown ins alignment a global perspective"

Connected through hyperedge HE-5 (induced by source paper "versatile land navigation using inertial sensors and odometry self calibration in motion alignment and positioning"):
  with members:
    - "observability of strapdown ins alignment a global perspective"

Connected through hyperedge HE-6 (induced by source paper "velocity position integration formula part ii application to strapdown inertial navigation computation"):
  with members:
    - "observability of strapdown ins alignment a global perspective"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.RO(Robotics)