To accommodate the presence of bounded biases in mixed-integer models, Khodabandeh (2022) extended integer estimation theory by introducing a new admissible integer estimator. The estimator follows the principle of integer least squares estimation and is computed via the integer search method of BEAT. In this contribution, we present the probability distributions of a class of estimators to which the proposed bias-constrained integer least squares estimation belongs. Some important interferometric measuring systems, whose estimation problems can be covered by BEAT, are identified. To show the proposed estimator at work, we apply BEAT to the problem of GLONASS single-differenced (SD) ambiguity resolution. Numerical results of several short-baseline datasets are presented to illustrate why one can achieve more accurate positioning solutions when considering between-receiver SD ambiguity resolution for the cases where carrier phase data are captured on frequency-varying signals with bounded SD receiver phase delays.

为了适应混合整数模型中存在的有界偏差，Khodabandeh (2022) 通过引入新的可接受整数估计器扩展了整数估计理论。估计器遵循整数最小二乘估计原理，并通过 BEAT 的整数搜索方法进行计算。在本文中，我们提出了所提出的偏差约束整数最小二乘估计所属的一类估计器的概率分布。确定了一些重要的干涉测量系统，其估计问题可以由 BEAT 解决。为了展示所提出的估计器的工作原理，我们将 BEAT 应用于 GLONASS 单差 (SD) 模糊度解析问题。给出了几个短基线数据集的数值结果，以说明为什么在考虑接收器间 SD 模糊度分辨率时，在具有有限 SD 接收器相位延迟的频变信号上捕获载波相位数据的情况下，可以实现更准确的定位解决方案。