Author Affiliations
1 School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China2 Wuhan Fisilink Microelectronics Technology Company Limited, Wuhan, Hubei 430074, Chinashow less
Fig. 1. Principle diagram of WLI-DOFVS system
Fig. 2. Flow chart of data processing
Fig. 3. Schematic of Mallat multiresolution decomposition
Fig. 4. Signals before and after denoising by wavelet threshold. (a) Original signal; (b) denoised signal
Fig. 5. Signal segmentation results of several typical intrusion events. (a) Footsteps of passerby; (b) bicycle; (c) knocking on fence; (d) cutting of optical cable
Fig. 6. Photograph of sensing fiber laying on fence and ground
Fig. 7. Typical features in time domain. (a) Average fragment interval; (b)fragment length; (c) PAR
Fig. 8. Energy distributions in frequency domain. (a) Footsteps of passerby; (b) bicycle rolling; (c) knocking on the fence; (d) cutting of optical cable
Parameter | Value |
---|
/km | 50 | /km | 1 | W /nm | ≈40 | P /dBm | 9.4 |
|
Table 1. Main parameters of WLI-DOFVS system
Intrusion event | Time domain feature +SVM | Frequency domain feature +SVM | Time/frequency domain feature +RBF NN | Time/frequency domain feature +SVM |
---|
Footsteps of passerby | 100 | 52.5 | 47.5 | 97.5 | Bicycle rolling | 75.0 | 97.5 | 100 | 100 | Knocking on fence | 90.0 | 97.5 | 87.5 | 100 | Cutting of optical cable | 100 | 72.5 | 87.5 | 95.0 | Average recognition rate | 91.25 | 80.00 | 80.63 | 98.13 |
|
Table 2. Recognition rate of 4 different methods for the 1st training set%
Intrusion event | Time domain feature +SVM | Frequency domain feature +SVM | Time/frequency domain feature +RBF NN | Time/frequency domain feature +SVM |
---|
Footsteps of passerby | 100 | 50.0 | 82.5 | 98.75 | Bicycle rolling | 90.0 | 95.0 | 97.5 | 95.0 | Knocking on fence | 85.0 | 95.0 | 87.5 | 100 | Cutting of optical cable | 100 | 60.0 | 72.5 | 100 | Average recognition rate | 93.75 | 75.00 | 85.00 | 98.50 |
|
Table 3. Recognition rate of 4 different methods for the 2nd training set%
Intrusion event | Time domain feature +SVM | Frequency domain feature +SVM | Time/frequency domain feature +RBF NN | Time/frequency domain feature +SVM |
---|
Footsteps of passerby | 100 | 52.5 | 52.5 | 100 | Bicycle rolling | 92.5 | 97.5 | 92.5 | 97.5 | Knocking on fence | 87.5 | 97.5 | 97.5 | 100 | Cutting of optical cable | 97.5 | 70.0 | 87.5 | 100 | Average recognition rate | 94.38 | 79.38 | 82.50 | 99.38 |
|
Table 4. Recognition rate of 4 different methods for the 3rd training set%
Intrusion event | Time domain feature +SVM | Frequency domain feature +SVM | Time/frequency domain feature +RBF NN | Time/frequency domain feature +SVM |
---|
Footsteps of passerby | 100 | 40.0 | 40.0 | 100 | Bicycle rolling | 85.0 | 90.0 | 95.0 | 97.5 | Knocking on fence | 85.0 | 97.5 | 95.0 | 100 | Cutting of optical cable | 100 | 65.0 | 55.0 | 100 | Average recognition rate | 92.50 | 73.13 | 71.25 | 99.38 |
|
Table 5. Recognition rate of 4 different methods for the 4th training set%
Intrusion event | Time domain feature +SVM | Frequency domain feature +SVM | Time/frequency domain feature +RBF NN | Time/frequency domain feature +SVM |
---|
Footsteps of passerby | 100 | 95.0 | 30.0 | 97.5 | Bicycle rolling | 92.5 | 97.5 | 95.0 | 100 | Knocking on fence | 75.0 | 90.0 | 82.5 | 92.5 | Cutting of optical cable | 97.5 | 2.5 | 42.5 | 95.0 | Average recognition rate | 91.25 | 71.50 | 62.50 | 96.25 |
|
Table 6. Recognition rate of 4 different methods for the testing set%
Recognition method | Mean /% | Variance /10-4 |
---|
Time domain feature +SVM | 92.63 | 2.04 | Frequency domain feature +SVM | 75.80 | 14.18 | Time/frequency domain feature +RBF NN | 76.38 | 87.20 | Time/frequency domain feature +SVM | 98.33 | 1.65 |
|
Table 7. Mean and variance of recognition rate of 4 different methods for the 5 groups of data