As one of the two key components of a mobile context (time and location), localization has been the subject of extensive works ranging from algorithms, models, and supporting technologies, to systems and applications. Current coarse-grained (room-level or meter-level) localization on a smartphone has enabled a lot of mobile services, such as location-based services, maps, and navigation systems. However, these services are severely limited when applied in more pervasive indoor environments due to low resolution. Indoor users can hardly navigate like those using outdoor GPS services. The major difference is as follows: meter-level (e.g. GPS with five-meter accuracy) localization is sufficient to navigate a car (meter-level footprint) on a street (several-meter footprint); but it is far from sufficient to navigate a user (foot-level footprint) in a library (with half-meter-wide isles and inch-level books) or a shopping mall (with inch-level items). Smartphone-based accurate “indoor GPS" or IPS (indoor positioning system) have been long awaited to improve indoor mobile services and enable new services. Despite significant efforts on indoor localization in both academia and industry in the past two decades [6,8,10,15,85,113], highly accurate and practical smartphone-based indoor localization remains an open problem. Some accurate localization solutions cannot be readily converted to smartphone-based ones due to various constraints.