Most track-to-track fusion (T2TF) algorithms for distributed tracking systems in the literature assume that the local trackers are synchronized. However, in the real world, synchronization cannot be usually achieved among distributed local trackers where local measurements are obtained and local tracks are updated at different times with different rates. In addition, communication links be-tween local trackers and the fusion center (FC) are subject to possible delays, which results in delayed local tracks for the fusion at the FC. This paper presents and compares algorithms for asynchronous Track-to-Track Fusion (AT2TF) for the fusion of asynchronous and delayed tracks. First, the optimal algorithm for AT2TF with no memory and with partial information feedback (AT2TFwoMpf) is presented. The algorithm, denoted as AT2TFwoMpfOpt, serves as the baseline algorithm for performance comparison. Three approximate AT2TF algorithms from the literature are compared with AT2TFwoMpfOpt and are shown to have consistency problems and loss in fusion accuracy. Then the Information Matrix Fusion (IMF) algorithm from the literature is generalized for the fusion of asynchronous tracks. Based on the generalized IMF (GIMF), AT2TF algorithms are derived for the information configurations with both partial and full information feedback. These algorithms are shown to have good consistency and nearly optimal fusion accuracy. Due to the simplicity of their implementation, these algorithms are appealing candidates for practical applications.