Can't find explaination of why frame to map data association resulting in inconsistency in the reference

[JaySlamer]

The reference 10 is VISUAL-INERTIAL NAVIGATION: A CONCISE REVIEW. Within it, I find no explaination. Maybe I somehow missed it. Could you help me by pointing it out.
According to my own understanding, if there is a big difference between the drifts of old and new keyframes, the built local map would be inconsistent, and it is likely the scan to map registration would be unstable or even fail. When we use keyframes that are close in terms of time, there is no such worry. However, we should use GPS and loop closure information to keep drift small anyway. When there is a big drift, inconsistency within local map is not my biggest concern, there is no point to continue the slam anyway. When we build local map using spatial information instead of a simple time window, it provides mid-term and long-term data association that is good to reduce drift. And slide-window approach introduces too many keyframes into the map its memory footprint grows quickly and unboundedly. So In my opinion, spatially local map is good for global consistency but bad for local consistency, slide window good for local consistency but bad for global consistency, and the former beats the latter hands-down in memory footprint.

[JaySlamer]

我用中文再解释下我的困惑。首先，按这个参考文献我没找到所谓激光雷达帧与地图匹配的不一致的解释，因此我也不知道作者所说的不一致和我认为的不一致是不是一回事。我对scan to map不一致的理解是：局部地图中有一些帧是老的帧，一些帧是新的帧，它们的漂移程度不同，所以不一致。这在我看来不是问题，这些老帧提供中长期数据关联，有利于把最近一帧的飘移减少，而新的帧有利于反映最新的动态变化，不失为一种很好的折中。而滑窗中都是新的帧，自然比较一致，但漂移没有人反应了，就导致问题不能得到解决。打个比方，就好比议会开会，所有人都一致热烈鼓掌，没有任何争吵，这绝不是好事。然而凡事都有个度，如果老帧新帧意见分歧过大，会直接导致点云配准崩坏，好比议会解散内战爆发，也不是好事。解决这个问题绝不是搞一党制（滑窗），把分歧从根源消灭，而是应该不断解决分歧（也就是飘移），避免矛盾积压到爆发。

[zxd123]

这里说的不一致指的并不是滑窗里的帧误差的不一致，而是估计得到的协方差与真实误差值的不一致，也就是在里程计中，位姿估计随时间出现了漂移造成误差越来越大，但是协方差(也就是对于当前位姿估计的置信度)并没有随之变大的情况。

[thlsealight]

这里说的不一致指的并不是滑窗里的帧误差的不一致，而是估计得到的协方差与真实误差值的不一致，也就是在里程计中，位姿估计随时间出现了漂移造成误差越来越大，但是协方差(也就是对于当前位姿估计的置信度)并没有随之变大的情况。

感谢解释，你的解释是我想要表达的意思，这里的不一致就是指的状态估计里面常说的不一致。论文初稿关于不一致这一块描述不够到位，具体等正式版论文。

谢谢！