25,000 715.7cBm 女18.7B 25.000 20.00 t-21.78 +20cm 20.000 60cm 15,.00 日B0cm %100en *-200行 0.00 -300m 5.000 02 35 0 0.4 0. 0.B 0-0050ara Fig.1. RSSI varies with transfer Fig.2.RSSI varies with transfer power Fig.3. Magnitude of RSSI swing in Fig.4.RSSI varies with the angle of distance CDF the reader tag 12000 12000 Reader antenna 10000 1000 8000 800 1 E000 6000 ② 0 400 0 2000 2001 Left Reader antenna 20 80 tag View rotation angle(degree) rotation angle(degree) Fig.5.Experiment deployment of Fig.6.RSSI varies with rotating the Fig.7.RSSI varies with rotating the Fig.8.Experiment deployment of rotating the reader tag around the axis tag in the plane rotating the tag C.RSSI Varies according to the Rotation of Tag Database RSSI varies little when the tag rotates around the axis, but RSSI varies as sine function when the tag rotates in the Data plane.Beside the orientation of the antenna,we consider the Locate processing orientation of the tag.We study two orientations of the tag method rotation,as shown in Fig.8.The first path is rotating the tag in the plane and the second represents spinning on the tag's control Scan Move and Rotate axes.We place a tag 2m in front of the antenna to conduct the experiments.As a result,Fig.6 represents spinning on the hardware Reader Robot axis,and Fig.7 represents rotating in the plane.We note that spinning on the axis has little influence on RSSI variation, but rotating in the plane changes RSSI like the sine function. Because the RSSI variation caused by the tag deployment may Fig.9.System architecture lead the indeterminate of the localization,we deploy our tag vertically to reduce the complexity. approaching.As shown in Fig.9,our localization system is D.Analysis consist of 3 main layers.Specifically,hardware layer includes all the devices,i.e.,reader and robot.And the control layer is According to the above results,we note several problems to be solved.We cannot estimate the accurate distance directly in charge of data interaction between the other two layers and from the RSSI value due to the noise.The antenna can identify conducting the command from the data processing layer.At the tag at the back,which will mislead the angle estimation. last,the data processing layer executes the localization method But we can still extracts opportunities from the results.RSSI and commands all the devices.With the architecture above,we are interested in how to locate to the object accurately with can provide the rough scope of the tag position and we can estimate the angle according to the RSSI variation pattern.The limited query duration in realistic environment. vertical deployed tag can reduce the complexity. VI.PATTERN BASED LOCALIZATION SOLUTION V.SYSTEM DESIGN Our pattern based localization solution contains four compo- In our system,objects are attached with an RFID tag for nents.Firstly,we scan the filed with Coarse-grained Rotation discontinuous identification.The RFID reader provides large to roughly determine the sector.Then we preprocess the sector transfer power range for dealing with different scenarios.To data with binary search to provide enough data for Fine locate automatically,we use a robot car to help rotating and Rotation.Thirdly,we do quadratic function fitting iteratively0 100 200 300 400 500 0 5,000 10,000 15,000 20,000 25,000 distance(cm) RSSI 15.7dBm 18.7dBm 21.7dBm 24.7dBm 27.7dBm 30.7dBm Fig. 1. RSSI varies with transfer distance 15 20 25 30 35 0 5,000 10,000 15,000 20,000 25,000 transfer power(dBm) RSSI 20cm 40cm 60cm 80cm 100cm 200cm 300cm Fig. 2. RSSI varies with transfer power 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 std/mean cdf Fig. 3. Magnitude of RSSI swing in CDF −150 −100 −50 0 50 100 150 0 2000 4000 6000 8000 10000 reader angle(degree) RSSI 1m 2m 3m 4m 5m Fig. 4. RSSI varies with the angle of the reader Fig. 5. Experiment deployment of rotating the reader 0 20 40 60 80 0 2000 4000 6000 8000 10000 12000 rotation angle(degree) RSSI 1m 2m 3m 4m Fig. 6. RSSI varies with rotating the tag around the axis 0 20 40 60 80 0 2000 4000 6000 8000 10000 12000 rotation angle(degree) RSSI 1m 2m 3m 4m Fig. 7. RSSI varies with rotating the tag in the plane Fig. 8. Experiment deployment of rotating the tag C. RSSI Varies according to the Rotation of Tag RSSI varies little when the tag rotates around the axis, but RSSI varies as sine function when the tag rotates in the plane. Beside the orientation of the antenna, we consider the orientation of the tag. We study two orientations of the tag rotation, as shown in Fig. 8. The first path is rotating the tag in the plane and the second represents spinning on the tag’s axes. We place a tag 2m in front of the antenna to conduct the experiments. As a result, Fig. 6 represents spinning on the axis, and Fig. 7 represents rotating in the plane. We note that spinning on the axis has little influence on RSSI variation, but rotating in the plane changes RSSI like the sine function. Because the RSSI variation caused by the tag deployment may lead the indeterminate of the localization, we deploy our tag vertically to reduce the complexity. D. Analysis According to the above results, we note several problems to be solved. We cannot estimate the accurate distance directly from the RSSI value due to the noise. The antenna can identify the tag at the back, which will mislead the angle estimation. But we can still extracts opportunities from the results. RSSI can provide the rough scope of the tag position and we can estimate the angle according to the RSSI variation pattern. The vertical deployed tag can reduce the complexity. V. SYSTEM DESIGN In our system, objects are attached with an RFID tag for discontinuous identification. The RFID reader provides large transfer power range for dealing with different scenarios. To locate automatically, we use a robot car to help rotating and Fig. 9. System architecture approaching. As shown in Fig. 9, our localization system is consist of 3 main layers. Specifically, hardware layer includes all the devices, i.e., reader and robot. And the control layer is in charge of data interaction between the other two layers and conducting the command from the data processing layer. At last, the data processing layer executes the localization method and commands all the devices. With the architecture above, we are interested in how to locate to the object accurately with limited query duration in realistic environment. VI. PATTERN BASED LOCALIZATION SOLUTION Our pattern based localization solution contains four compo￾nents. Firstly, we scan the filed with Coarse-grained Rotation to roughly determine the sector. Then we preprocess the sector data with binary search to provide enough data for Fine Rotation. Thirdly, we do quadratic function fitting iteratively