Research On Bistatic High Frequency Radar Data Processing NFE Technology

High Frequency Surface Wave Radar (HFSWR) works in the short wave band which has crowded frequencies and complicated electromagnetic environments, so its detection performance is susceptible to the ionosphere interference change. The system detection is difficult to guarantee the continuity of the target measurements, and the low azimuth resolution causes the deconcentration and jump of the detected plots. So it is a tough work to initiate target tracks and form stable ones while processing data. However, bistatic/multistatic HF radars are one of the approaches which could increase all-weather performance of monostatic HF radars and ensure the track initiation and forming effective tracks under complicated electromagnetic environments. The track initiation and short track composition under complicated electromagnetic environments is principally researched based on T/R-R bistatic HFSWR system and the intelligentized information fusion models and algorithms is proposed in this paper.According the characteristic that the vertical polarized electromagnetic wave diffracts along the ocean surface, the detection range and localization precision for T/R-R bistatic HF radar system are deduced and simulated using the curved face positioning analysis method, including drawing localization precision curves using single/multiple measurement subsets and the distribution diagram of high precision measurement subsets is obtained. These analyses make the proposing of data processing method based on bistatic HF radar system have pertinence and provide referenced proofs.Affected by the complicated electromagnetic environment, sea clutter and ionospheric clutter, the plots detected by HFSWR have the characteristics of saltation, nonuniformity, deficiency and regionality. The issues above are summarized to be the fusion problems of the uncertain information for bistatic HFSWR system in this paper from the angle of signal processing. The solving of this sort of problems needs to introduce intelligentized information fusion models and algorithms in order to structure a high-powered intelligentized information fusion system in possession of learning, reasoning and expert function. A tightly-coupled NFE model combined with Neural network, Fuzzy reasoning and Expert system is constructed based on neural network-fuzzy reasoning model by introducing expert system technology. It is indicated that this model can be regarded as a category of complete intelligentized information fusion model possessing commonality and approximation and it is adaptive to process the uncertain information fusion problems under complicated environment.The velocity precision is far higher than that of range and direction, so the velocity information takes a significant part in the association processing. It is unavailable to realize velocity coordinate transformation while processing measurement association in bistastic HFSWR in order that the actual velocity information could not be directly utilized, so this make it intractable to choose the position and size of the initial association gate. Aiming at this problem, the initial association gate forecasting NFE model based on single detected plot is proposed in this paper. In this model, the radial gradient (determined by the target position information) and radial velocity are set to be input variables and the predicted movement region in radial coordinate system is set to be output variable. According to the different detection precision for bistatic HFSWR the member functions subject to diverse regions are determined by establishing expert system to realize initial association gate forecasting in order to solve the difficult problem of forecasting target movement trend only depending on the first radar echo for bistatic HFSWR system. This method have not increased the calculation quantity profiting from the parallel processing of neural network as well as increasing the hypothetical gate numbers, so it ensures to determine the initial association gate and initiate tracks opportunely and exactly.The commonness of traditional track initiation methods is: firstly, they all utilize the position information (including radial range and azimuth angle) to make determination and then consider the velocity association; secondly, the criterion for judging whether forming valid tracks is according to the linearity degree of the link line of measurements. This is quite proper and effective for high precision radar system. However, the inherent characteristic of HFSWR determines low detection precision of target position accuracy and this makes the plot data saltation, nonuniformity, deficiency and regionality so that traditional algorithms could not initiate tracks efficiently, and this problem has stood out and desiderates solutions. Based on the considerations above, an NFE track initiation method is proposed from a brand-new angle and idea after a particular analysis of the data features for bistatic HFSWR. It has built the fuzzy relationship between the radial velocity change, radar cross section change and signal to clutter ratio magnitude and the degree of belief for the target measurement which is regarded to confirm the update in the proposed method and the position data are utilized indirectly to choose the corresponding member functions of input variables as the judgement conditions of the expert system, so as to solve the low track initiation probability problems under the circumstance of intermittent measurements in bistatic HFSWR system.HFSWR adopts super-resolution and high-precision Doppler processing technology other than ordinary microwave radar, therefore, how to get sufficient use of Doppler frequency shift parameter is the key of the track processing for bistatic HFSWR. In respect that tracks from each receiver are usually intermittent and short rather than compete and steady, the track fusion for bistatic HFSWR is actually a short track composition issue. Aiming at this situation, the Doppler-NJPDA data association method utilizing doppler frequency shift difference to revise the conditional probability of the public measurements from the targets is proposed to increase measurement-to-track association probability in the intersection of the cross moving targets in the dense false measurements environment in order to solve the true-or-false measurements identification problem of the cross moving targets for bistatic HFSWR. In addition, the adaptive tracking gate algorithm based on detection precision of bistatic HFSWR is proposed in short track composition processing affiliated the NFE track initiation method, and the modified update degree of belief NFE model is used to eliminate the outliers. Integrating the method above, the real-time operation and reliability measurement-to-track association is ensured so as to solve the short track composition problem of the cross moving targets in the intersection for bistatic HFSWR.