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重复水准测量提供了点位高程变化的重要几何信息，但水准测量本身又受地球重力场的影响，在水准观测值中同时含有重力场的信息．重复绝对重力测量或相对重力测量提供了丰富的局部重力场的信息，由于点的重力值随高程变化而变化，因此，它们同时也含有点位高程变化的信息．经典平差方法将两类观测值分别解算，将互补的信息作为干扰加以改正，或作为噪声处理，这不仅丢失了有用的信息，而且有损于成果的精度．本文在整体大地测量框架内构制了这两类观测值的联合解算模型，给出了解算方法，研究了形变场的拟合和预测问题，并用实例进行了验证，得到了一些有益的结果．研究表明：联合解算可同时给出地面点的高程及其变化率和局部重力场的参数及其变化率，有利于信息的提取；联合解算的精度优于单独解算的结果；秩亏抗差解和拟稳抗差解分别优于相应的非抗差解；拟稳抗差解算方法自动选择拟稳点，有效地抵制了粗差和形变异常对起算基准的干扰；对于多期复测的资料，使用动态拟稳抗差估计，不仅能动态地寻找可靠的拟稳点，而且能保证动态变化参数免受或少受各历元观测粗差的干扰，可明显地提高动态参数的验后精度；当点位丰富时，建立形变模型并据此内插未测点的变形和推测某个时刻地壳的形变状态也是可行的．
Repeated level measurements provide important geometric information about the elevation of a point, but the level measurement itself is influenced by the Earth's gravitational field, which contains information about the gravity field in the level observations. Repeated absolute gravimetric or relative gravimetric measurements provide abundant information about the local gravitational field. Since the gravitational values of the points vary with the elevation, they also contain information about the elevation of the points. The classical adjustment method solves the two types of observations respectively, corrects the complementary information as interference or as noise, which not only loses useful information but also detracts from the accuracy of the result. In this paper, a joint solution model of these two types of observations is constructed in the framework of global geodesy. The solution method is given, the fitting and prediction problems of deformation field are studied, and examples are used to verify and some beneficial results are obtained . The results show that the joint solution can give both the elevation and its rate of change of the ground point and the parameters of the local gravitational field and its rate of change, which is beneficial to the information extraction. The accuracy of the joint solution is better than that of the solitary solution alone. Resisting and quasi-steady solutions are respectively better than those without corresponding solutions. Quasi-stationary solutions are automatically chosen to stabilize them, which effectively counteract the interference caused by gross errors and deformation anomalies. The retest data, using the dynamic quasi-stationary robust estimation, can not only find reliable quasi-stationary points dynamically, but also ensure that the dynamic parameters are protected from or less disturbed by the gross errors of various epoch observations and can obviously improve the dynamic parameters When the point is rich, it is feasible to establish the deformation model and interpolate the unmeasured points and estimate the deformation state of the crust at a certain moment.