There are different kinds of noise in the optical gyro output signals. The signals imbedded noise are always
non-stationary. Recent works have demonstrated that the noise can be separated from the original signal by the empirical
mode decomposition (EMD). However, there are some shortages in the original algorithm of EMD, for example, the
envelope mean computation and the time-consuming fitting. An improved EMD is introduced where quasi-mean filter
and the extension segment approximation are proposed. The new EMD is used in ring laser gyro signal analysis and
de-noising, and the Allan variance is used to evaluate the result.
A high accuracy line-of-sight (LOS) Stabilization system based on digital control technology was designed. The
current feedback closed-loop system was introduced which uses the CCD graphic and resolver to constitute the position
closed-loop and uses the optic fiber gyro to constitute the rate closed-loop. In order to realize zero steady-state error of
angular output in counteracting disturbance from carrier, a PII2 (proportional-integral-double integral) control scheme is
proposed. The hardware configuration and software system is presented. Experimental results show that the system has
perfect dynamic and static performance and the technical requirements were satisfied.
A new algorithmic for strapdown inertial navigation system (SINS) state estimation based on neural networks is
introduced. In training strategy, the error vector and its delay are introduced. This error vector is made of the position and
velocity difference between the estimations of system and the outputs of GPS. After state prediction and state update, the
states of the system are estimated. After off-line training, the network can approach the status switching of SINS and
after on-line training, the state estimate precision can be improved further by reducing network output errors. Then the
network convergence is discussed. In the end, several simulations with different noise are given. The results show that
the neural network state estimator has lower noise sensitivity and better noise immunity than Kalman filter.
Audio Video coding Standard (AVS) is a new audio and video coding standard in China, in which variable block sizes and quarter-pixel motion estimation have been applied to improve coding efficiency. In this paper, an adaptive search range based quarter-pixel search algorithm is proposed to further speed up the encoding process and reduce the computation complexity. Small diamond search and threshold judgment are adopted in this algorithm. Compared to the full sub-pixel search algorithm, experiments show that the proposed algorithm can reduce the sub-pixel search point by 30.25% on average with the limited performance lose about 0.0093dB. And compared to the fast search algorithm in AVS reference software, experiments show that the proposed algorithm can reduce the sub-pixel search point by 8.78% on average with the performance achieve a gain up to 0.0221dB.
A 2-position analytic alignment method for strapdown inertial navigation system (SINS) is developed to overcome the
limit on precision in analytic alignment on stationary base, which mainly comes from the performance of inertial
measurement unit (IMU). IMU is successively rest at two positions by rotating the vehicle to measure the earth's rotation
rate and gravity, and measurement at one position is subtracted from the other to eliminate constant error of IMU to
improve alignment precision. Transformation matrix between two vehicle reference frames is calculated using output of
gyros during the vehicle's rotation. An improved method for estimating gesture matrix is developed to avoid matrix
nonreversibility. Error analysis is performed to determine the available precision which is demonstrated by computer
simulation.
Gyro output signal is a non-stationary and time-varied time series mixed with noise. A new time-frequency analysis
method for gyro de-noising, the empirical mode decomposition (EMD), is introduced. The non-stationary hybrid gyro
signal is studied adaptively in the domain of time and frequency. First the hybrid signal is decomposed into finite
intrinsic mode functions (IMF), then their frequency characteristic and the relationship between these IMFs and different
gyro errors are studied deeply. Follow that a certain number of IMFs are eliminated and EMD's filter bank characteristic
is achieved. After the ring laser gyro signal is processed by EMD and wavelet, Allan variance approach is applied to
evaluate five kinds of gyro noise. By the conclusion, the EMD method is obviously more efficacious than wavelet in
eliminating various kind of noise.
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