ANALYSIS AND RECOVERY OF SYSTEMATIC ERRORS IN AIRBORNE LASER 
SYSTEM 
Zhihe Wang*, Rong Shu ,Weiming Xu, Hongyi Pu, Bo Yao 
Shanghai Institute of Technical Physics, CAS, 500 Yutian Road, Shanghai 200083, P. R. of China - 
zhhwang@mail.sitp.ac.cn 
Commission VI, ICWG V/I 
KEY WORDS: Airborne laser system, System errors, Error recovery, adjustment model, Surface extraction 
ABSTRACT: 
Although some mature manufactures of airborne laser system (ALS) have been published for some years, however, in china, the 
development of ALS just is on the starting step. Shanghai Institute of Technical Physics (SITP), CAS is developing a new airborne 
laser instrument. It is the best difficult task to determining the systematic biases of ALS. The ultimate goal is to determine the master 
systematic errors and to correct the raw laser points. By analyzing the systematic error source firstly, the adjustment model presented 
in paper enable modelling and removing the actual errors in laser point sets. Interesting surfaces and regions can be determined by a 
least-squares plane fit through a subset of laser points. The proposal model of solution is based on integrating the observations and 
adequate control planes and the redundancy in the overlapping areas of laser data sets. It has been demonstrated that moderate slopes 
are sufficient to generate reliable solutions. In addition, the precision of ranging and scan angle aiming to the same target point is 
tested by laboratory experiment at the end of paper. 
1. INTRODUCTION 
Although some mature manufactures of airborne laser scanning 
(ALS) have been published for some years, however, in china, 
the development of ALS just is on the starting step. Shanghai 
Institute of Technical Physics (SITP), CAS is developing a new 
airborne laser instrument. Its laser pulse rates have achieved 
50k Hz and its scan rates have 40 Hz. It is capable of recording 
multi return signal instead of either the first or the last return. It 
provides a 3D point cloud as a primary product. The 
achievements in developing appropriate ALS data processing 
software, however, have been rather marginal. 
It is the best difficult task to determining the systematic biases 
of ALS. The ultimate goal is to determine the master systematic 
errors and to correct the raw laser points such that only random 
errors are left. The factors affecting laser-target position 
accuracy are numerous. Huising and Gomes Pereira (1998) 
report about systematic errors of 20 cm in elevation and of 
several meters in position between overlapping laser strips, 
Crombaghs et al. (2000) identify systematic trends between 
overlapping strips. 
Apart from the target reflectivity properties and laser-beam 
incidence angle, the main limiting factors are the accuracy of 
the platform position and orientation derived from the 
carrier-phase differential GPS/INS data and uncompensated 
effects in system calibration. The calibration can be divided 
into that of calibration of individual sensors such as the laser 
range-finder and that concerning spatial (lever-arm) or 
orientation (bore-sight) offsets between the sensors due to a 
particular assembly. In most system installations, the 
lever-arms between LiDAR-IMU-GPS sensors can be 
determined separately by independent means, although this 
represents certain difficulties related to the realization of the 
IMU body frame. On the other hand, the determination of the 
bore-sight angles is only possible in-flight once the 
GPS/INS-derived orientation becomes sufficiently accurate. 
The existing calibration procedures, while functional, are 
recognized as being sub-optimal since they are labor-intensive 
(i.e., they require manual procedures), non-rigorous and 
provide no statistical quality assurance measures. Furthermore, 
the existing methods often cannot reliably recover all three of 
the angular mounting parameters. The problem is worsened by 
the angular uncertainty due to the broad laser beam width 
(Lichti, 2004). On the other hand, the cross-section method 
seems to be popular in commercial systems and usually 
provides satisfactory results for the bore-sight estimate in the 
roll direction. However, its use for the recovery of pitch and 
yaw/heading direction is less appropriate. The use of the slope 
gradients in DTM/DSM for bore-sight estimation made its way 
to a popular software package used for ALS data handling 
(Soininen and Burman, 2005). The principal weakness of this 
approach is the strong correlation of the bore-sight angles with 
unknown terrain shape. Also, the implemented stochastic model 
of the LiDAR trajectory assumes time-invariant behavior of 
the GPS/INS errors that is not realistic. 
Figure 1. Illustration of scan angle errors