A new generalized optimum strapdown algorithm with coning and sculling compensation is presented, in which the position, velocity and attitude updating operations are carried out based on the single-speed structure in which all computations are executed at a single updating rate that is sufficiently high to accurately account for high frequency angular rate and acceleration rectification effects. Different from existing algorithms, the updating rates of the coning and sculling compensations are unrelated with the number of the gyro incremental angle samples and the number of the accelerometer incremental velocity samples. When the output sampling rate of inertial sensors remains constant, this algorithm allows increasing the updating rate of the coning and sculling compensation, yet with more numbers of gyro incremental angle and accelerometer incremental velocity in order to improve the accuracy of system. Then, in order to implement the new strapdown algorithm in a single FPGA chip, the parallelization of the algorithm is designed and its computational complexity is analyzed. The performance of the proposed parallel strapdown algorithm is tested on the Xilinx ISE 12.3 software platform and the FPGA device XC6VLX550T hardware platform on the basis of some fighter data. It is shown that this parallel strapdown algorithm on the FPGA platform can greatly decrease the execution time of algorithm to meet the real-time and high precision requirements of system on the high dynamic environment, relative to the existing implemented on the DSP platform.
References
[1]
Savage, PG. Strapdown inertial navigation integration algorithm design. Part 1: Attitude algorithms. J. Guid. Control Dyn 1998, 21, 19–28, doi:10.2514/2.4228.
[2]
Titterton, DH; Weston, JL. Strapdown Inertial Navigation Technology, 2nd ed ed.; AIAA: Reston, VA, USA, 2004.
[3]
Savage, PG. Strapdown Analytics, 2nd ed ed.; Strapdown Associates, Inc: Maple Plain, MN, USA, 2007.
[4]
Bortz, JE. A new mathematical formulation for strapdown inertial navigation. IEEE Trans. Aerosp. Electron. Syst 1971, 7, 61–66, doi:10.1109/TAES.1971.310252.
[5]
Miller, RB. A new strapdown attitude algorithm. J. Guid. Control Dyn 1983, 6, 287–291, doi:10.2514/3.19831.
[6]
Lee, JG; Yoon, YJ. Extension of strapdown attitude algorithm for high-frequency base motion. J. Guid. Control Dyn 1990, 13, 738–743, doi:10.2514/3.25393.
Musoff, H; Murphy, JH. A study of recent strapdown navigation attitude algorithms. Proceedings of AIAA Guidance, Navigation and Control Conference, Monterey, CA, USA, 9–11 August 1993; pp. 1717–1723.
[9]
Ignagni, M. Efficient class of optimized coning compensation algorithms. J. Guid. Control Dyn 1996, 19, 424–429, doi:10.2514/3.21635.
[10]
Park, CG; Kim, KJ; Chung, D; Lee, JG. Generalized coning compensation algorithm for strapdown system. Proceedings of AIAA Guidance, Navigation and Control Conference, San Diego, CA, USA; 1996.
[11]
Park, CG; Kim, KJ. Formalized approach to obtaining optimal coefficients for coning algorithms. J. Guid. Control Dyn 1999, 22, 165–168, doi:10.2514/2.7620.
[12]
Ignagni, MB. Duality of optimal strapdown sculling and coning compensation algorithms. Navigation 1998, 45, 85–95.
[13]
Roscoe, KM. Equivalency between strapdown inertial navigation coning and sculling integrals/algorithms. J. Guid. Control Dyn 2001, 24, 201–205, doi:10.2514/2.4718.
[14]
Savage, PG. Strapdown inertial navigation integration algorithm design. Part 2: Velocity and position algorithms. J. Guid. Control Dyn 1998, 21, 208–221, doi:10.2514/2.4242.
[15]
Savage, PG. A unified mathematical framework for strapdown algorithm design. J. Guid. Control Dyn 2006, 29, 237–249, doi:10.2514/1.17112.
[16]
Savage, PG. Computational Elements for Strapdown Systems, Available online: http://ftp.rta.nato.int/Public/PubFullText/RTO/EN/RTO-EN-SET-064/EN-SET-064-03.pdf (accessed on 4 July 2011).
[17]
Savage, PG. Coning algorithm design by explicit frequency shaping. J. Guid. Control Dyn 2010, 33, 1123–1132, doi:10.2514/1.47337.
[18]
Musoff, H; Murphy, JH. Study of strapdown navigation algorithms. J. Guid. Control Dyn 1995, 18, 287–290, doi:10.2514/3.21382.
[19]
Xie, X; Guo, M-F; Zhou, B. Design of system for high performance navigation computer system base on dual DSPs & FPGA. Control Autom 2009, 25, 1–2.
[20]
Jew, M; El-Osery, A; Bruder, S. Implementation of an FPGA-based aided IMU on a low-cost autonomous outdoor robot. Proceedings of IEEE/ION Position Location and Navigation Symposium (PLANS 2010), Indian Wells, CA, USA, 4–6 May 2010; pp. 1043–1051.
[21]
Jia, SW; Feng, D-Z; Wang, M-G. The reserch on algorithm for SINS based on FPGA. J. Proj. Rocket. Missiles Guid 2006, 26, 953–955.
[22]
Yang, F; Hao, Y-P; Miao, L. Based on FPGA by constructed multi-processor navigation system design. J. Proj. Rocket. Missiles Guid 2007, 27, 126–128.
[23]
Geng, YR; Wang, YZ; Cui, ZX. Optimal design for sculling algorithms of SINS. J. Beijing Univ. Aeronaut. Astronaut 2001, 27, 694–697.
[24]
Grejner-Brzezinska, DA; Yi, Y; Toth, C; Anderson, R; Davenport, J; Kopcha, D; Salman, R. Enhanced gravity compensation for improved inertial navigation accuracy. Proceedings of 16th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS/GNSS 2003), Portland, OR, USA, 9–12 September 2003.
[25]
Kwon, JH; Jekeli, C. Gravity requirements for compensation of ultra-precise inertial navigation. J. Navig 2005, 58, 479–492, doi:10.1017/S0373463305003395.
[26]
Akeila, E; Salcic, Z; Swain, A. Direct gravity estimation and compensation in strapdown INS applications. Proceedings of 3rd International Conference on Sensing Technology, Tainan, Taiwan, 30 November–3 December 2008.
[27]
Groves, PD. Principles of GNSS, Intertial, and Multisensor Integrated Navigation Systems; Artech House: Norwood, MA, USA, 2008.
