## 1 Introduction
Compared with the AR procedure in GNSS standalone systems, not only are the pseudorange and carrier-phase measurements utilized as observables, but also the position vectors derived from the INS solution are taken as additional observables to solve this LS problem. This inertial-aided AR algorithm is expected to obtain more precise estimation and reduce the search space under INS motion constraints. Moreover, it only uses the observations of the current epoch, so the second kind of implementation is not affected by the intermittent GNSS reception. However, since both implementations search integer solutions in the ambiguity domain, the success rate of AR is unavoidably dependent on the quality of pseudorange measurements. When the pseudorange measurements have large errors due to multipath, the accuracy of the above two kinds of tight integration techniques will be degraded. Therefore, in order to obtain high precision positioning results continuously in urban environments where satellites frequently change and large pseudorange errors exist, this paper proposes a new implementation of the tightly coupled RTK/INS integration. The new tightly-coupled algorithm proposed in this paper still contains the two stages: INS-aided AR and a correction step. However, in order to avoid the influence of large pseudorange errors in float ambiguity estimation, we perform the AR process in the Position Domain. Thus, the proposed algorithm will be abbreviated as \"ARPD-RTK/INS\" in the following sections. In our INS-aided AR process, the INS solution is used to provide a more accurate initial value of location and a more efficient search volume due to the use of motion constraints, when compared with the standalone-GNSS AR techniques in the position domain [4; 12]. To get rid of the influence of the pseudorange error, we determine to use the posterior probability density function (PDF) to represent the weights of candidate points. Taking into account the integer property of the carrier-cycle ambiguity, the posterior PDF is only updated by the double-differenced carrier-phase measurements of GPS and BDS, which does not involve pseudorange measurements. Furthermore, we expect that a suboptimal integer solution can be obtained in the AR process, which is able to provide more precise ranging information than the pseudorange for the ensuing correction step, even if it is not necessarily the fixed integer solution. Thus, the ultimate solution is obtained by the weighted average of candidate ambiguity vectors instead of finding the fixed integer solution with the maximum probability. This paper is organized as follows. Section 2 describes the architecture of conventional RTK/INS integrations and the transition and observation models on which to base our positioning process. Section 3 illustrates the flow chart of the new ARPD-RTK/INS algorithm, and explains the steps to solve the integer ambiguities in the position domain. Section 4 presents the experimental results of the proposed algorithm, and evaluates the performance by comparing with other algorithms on both real and simulated datasets. Section 5 summarizes our conclusions and future research directions.