Passive multiple target indoor localization based on joint interference cancellation in RFID system

Passive indoor localization has been researched for many years[1]-[4].The goal of this challenging problem is to estimate the coordinates of targets which do not carry any auxiliary devices. The radio frequency identification (RFID) technology presents an efficient and low-cost indoor localization solution. The pioneers mostly focused on the localization methods for RFID reader [5], tags [6], or single tag-free target [7]. These kind of methods are excellent but unsuitable for the passive multiple target scenario. There are two main problems. One is the effect of interference that came from the array and among targets. The other is how to distinguish the coherent signals, in other words, to estimate the number of targets from the superimposed received signal. Some traditional methods such as the akaike information criterion (AIC) and gerschgorin disks estimation (GDE) [8] are disable to estimate the number of coherent signals. The sub-space methods like space smoothing (SS) MUSIC algorithm [9] can distinguish the multiple incident coherent signals efficiently only in the far field assumption but become almost invalid in the near field indoor environment.

Recently, for the passive multiple target localization, channel blocking or shadowing loss [10], [11] was analyzed and utilized. The transmitters and receivers were deployed densely as the uniform linear arrays to make the measured area almost full of the line of sight (LOS) propagations. The changes of channel parameters indicate the position information. Radio tomographic imaging (RTI) method [12], which is inspired from medical and geophysical imaging systems, is also based on shadowing loss. The measured area was divided into small pixel and the shadowing loss is approximated as a weighted summation of attenuation of each pixel [13]. The ellipsoid weighted model [14] was used to determine the weight of each link. However, the “interest range” of channel blocking is small. The target, which is more than 15.8cm away from the LOS path, will have no effect on the received signal strength (RSS) at 2.4 GHz frequency [15]. This means a large number of transceiver nodes to ensure the coverage of LOS in the measured area. Besides, the method based on channel blocking also need to match the paths with targets, and this process is usually computational infeasible [16]. 

Against this background, we propose a passive multiple target localization utilizing the diffuse reflection of the targets. Spatial spectrum was calculated by 2-Dimensional maximum likelihood function and a joint interference cancellation method was introduced to make spatial spectrum work well. Uniform circle array (UCA) of reference tags were deployed instead of uniform linear array (ULA) to reduce the aperture limitation. A carefully designed relative position of adjacent reference tags and a modified channel model were combined to reduce the mutual coupling. At last, a virtual distributed radar was constructed to reduce false positive and false negative estimations.