|
Data Compression of Airborne Laser Scanner Data
3-2. Analysis of the GPS/IMU data
GPS/IMU data file consists of observed GPS data and IMU data. GPS data and IMU data was separated by internal format, and most suitable compression method was determined from the characteristics of each data. Fig. 6 and 7 show the frequency of x-axis acceleration and angle acceleration data by difference method, respectively. From the same analysis of 3 axes acceleration and angle acceleration, effective entropy effects were obtained by using the linear difference method.  Fig. 6. Frequency of x-axis acceleration and the difference data.  Fig. 7. Frequency of x-axis angle acceleration and difference data. 4. The adopted compression method Table 4 shows the compression method using in this study. The method for each compression method is following. The i-th laser launch time data, mirror angle data, and GPS/IMU data is yi and return pulse data at the time t is Pt. The linear difference (Di) of GPS/IMU data expressed as equation 1is preserved. Di = yi yi-1 (1) The quadratic difference (DDi) of laser launch time and mirror angle data expressed as equation 2 is preserved. DDi = Di Di-1 (2) Fig. 8 shows the original data of the return pulse data. The existing probability of high-level return pulse data is low, and the compression effects by the difference method between same-level return pulse data are not sufficient. So the difference method dividing 2-axes of pulse time (difference between same array data) and n-th return pulse (difference between same line data) was selected. When the difference data of n th array at pulse time t is Dnt, the linear difference data of 1st array is calculated by equation 3, and return pulse data after 2nd array is calculated by equation 4 and 5. D1t = P1t P1t-1 (3) D2t = P2t P1t (4) D3t = P3t P2t (5) The method preserved the difference data by such equation is defined as the combination difference method between time and pulse Fig. 9 shows the flow of the process. In actual processing, the data converted by each compression method is output as the compression data through the coding process (PPMD method).
 Fig. 8. The original data of the return pulse data.  Fig. 9. The flow of the process. 5. Results Table 5 shows the comparison between the proposed method and the general method for pulse data. Table 6 shows the compression results of airborne data using the compression method in this study. From these results, the higher compression result for the laser data is obtained from the proposed method than the general method. It is confirmed that the compression ratio necessary to transmit on real time (20 %) is accomplished in this method.
6. Conclusions The compression method proposed in this study is used at airborne observation, the time lag from data acquisition to landing is canceled, and it is useful in the cases at the time of the disaster. Although the loss-less compression method is adopted now, we examine the compression method which removes noise data on ground process, and improves to fit this compression method also to the data acquired at the higher pulse rate to transmit the data earlier. References
Page 3 of 3
| Previous | |