Loran-C is the most essential backup and supplementary system for the global navigation satellite system (GNSS). Continuous wave interference (CWI) is one of the main interferences in the Loran-C system, which will cause errors in the measurement of the time of arrival, thereby affecting positioning performance. The traditional adaptive notch filter method needs to know the frequency of CWI when removing it, and the number is limited. This paper presents a method based on sparseness to suppress the CWI in the Loran-C signal. According to the different morphological characteristics of the Loran-C signal and the CWI, we construct dictionaries suitable for the two components, respectively. We use the tunable Q-factor wavelet transform and the discrete cosine transform to make the two components obtain a good sparse representation in their respective dictionaries. Then, the two components are separated using the morphological component analysis theory. We illustrate this method using both synthetic data and actual data. A huge advantage of the proposed method is that there is no need to know the frequencies of the CWI for it can better cope with frequency changes of the CWI in the actual environments. Compared with the adaptive notch filter method, the results of the proposed method show that our approach is more effective and convenient.
In consideration of the problem that traditional geomagnetic aided navigation method cannot reduce the scaling error of indication track in inertial navigation system (INS), which will further limit the error correction precision of gyro and accelerometer, an improved geomagnetic matching algorithm based on affine transformation is proposed in this paper. A geomagnetic matching algorithm led to the optimal affine transformation solution by Procrustes analysis is presented and develops latitude and longitude reference information. Then a 13-dimensional-state extended Kalman filter which estimates the attitude misalignment angles, the position error, the velocity error, the Gyro drift, and accelerometer error is introduced to continuously update the output of INS and remove the accumulative error. The results show that geomagnetic aided navigation based on improved algorithm has better location accuracy and correction accuracy of INS than the traditional method.
This paper proposes using Finite Element Analysis (FEA) simulations to optimize the design structure for low-frequency Magnetically Shielded Rooms (MSRs). In constructing a multi-layer MSR, the different characteristics of the material and laminated structure will bring different levels of magnetic Shielding Effectiveness (SE). The theoretical SE of an MSR can be determined quickly. By using the method used in this paper, the ideal laminated material structure can be found without increasing the MSR construction cost. According to the simulation results and the actual MSR measurement results we built, the optimized MSR design structure can improve the SE by 13 dB. In the area where the external measurement magnetic field is 37 820 nT, the magnetic field in the MSR is as low as 28 nT, and the SE of the MSR is higher than 57.3 dB. The method proposed by this research can provide the theoretical basis for optimal design structure and the FEA simulation method for engineering practice, which can effectively improve the SE of shielded rooms and save the construction cost. The FEA simulations used in this paper can be obtained from the following URL: https://github.com/YuukiAsuna/-Finite-element-simulation-of-material-lamination-sequence .
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