中文摘要：

本文研究参数带有不等式约束平差模型的一种新算法。采用的方法是先将参数带有不等式约束的最小二乘问题转换成凸二次规划问题,然后利用二次规划的Kuhn-Tucker条件把二次规划问题转换成线性互补问题（LCP）,从而求得参数最小二乘估计的一般形式,并给出算法,便于在实际测量中应用。

英文摘要：

This paper studies adjustment model witb inequality constrained parameters, and puts forward a new algorithm for it In this algorithm, inequality constrained leastsquare problems are first translated to convex quadratic programming problems and then translated to the linear complementarity problem （LCP） using Kuhn Tucker conditions of quadratic programming, which consequcntly gives the general form of least squares estima tion in adjustment model, as well as the algorithm is simple and easy to understand. A comparative calculation on a simulation example indicates that this algorithm can be applied to adjustment computation in the practical measurement.