Research And Implementation On Space-Time Joint Based Feature Extraction And Synthetical Processing Of JTIDS Signal

In integration with JTIDS signal characteristic, this thesis deeply studies the technology of JTIDS users'fine feature extraction and synthetical processing based on space-time joint, designs the corresponding scheme, constructs software platform of users storing under the circumstances of VC, and verifies the feasibility and validity of scheme using mounts of simulation data. The primary work is summarized as follows:1. The channels model of JTIDS signal is built. In this model, factor K and doppler frequency offset are extracted separately with rician envelope estimator and covariance estimator. Simulation results show that the estimation performance of factor K and doppler frequency offset is stable, which makes them space-domain fine features.2. Spatial location feature is extracted using high-precision spectral-correlation time difference estimation method combined TDOA target position algorithm. Traditional positioning solver algorithms are improved based on data fusion, and multi-algorithm co-location model is constructed. Based on co-location model above, the estimation algorithm is designed. Simulation results show that improved algorithm has better estimation precision than the former.3. In order to extract the non-linear feature of different users in time-domain based on the direct bispectrum estimation algorithm and indirect bispectrum estimation algorithm, bispectrum estimation algorithm based on local surrounding-line integral is studied. High Fisher degree of separability local surrounding-line integral bispectrum is chosen as the sorting feature. Simulation results show that bispectrum estimation algorithm based on local surrounding-line integral has better estimation performance than that of the direct or indirect bispectrum estimation.4. Frequency hopping communication system is adopted in JTIDS signal, and the differences of frequency hopping parameters reflect fine differences of different JTIDS users. So, frequency hopping period is extracted by WVD, PWVD, SPWVD and MSPWVD. Simulation results show that frequency hopping period is extracted by MSPWVD algorithm is superior to others. It is a steady algorithm for frequency hopping period extraction.5. Space-Time feature is synthetically processed through feature preprossessing, single dimension separation analyzing and feature syncretizing. The corresponding scheme is designed, and then, the software platform of users storing is built, and the scheme is verified using a great deal of simulation data. Simulation results show that the scheme can satisfy the user sorting demand of the JTIDS signal based on space-time synthetical processing, and that it has better sorting performance.