Research On Waveform For Multitargrt Detection Of Radar Sensor Network

Radar Sensor Networks(Radar Sensor Networks, RSNs) comprise multiple radar sensors(RSs), which can be categorized as distributed RSN system and centralized RSN system. Compared with centralized one, the distributed RSN owns the advantages such as engineering tractability, high systematic sensitivity and subdued hidded effect. Therefore, it has wide applications and a promising future in a variety of fields like military, transportation and so on. The ability of multi-target resolution and detection, the synthesized performance of the system, has a direct impact on the corresponding important performance like systematic sensitivity and accuracy. However, the consideration for RSN systems multi-target of distribution and identification in radar transmit waves of RSN has not been discussed extensively.In order to solve the above problems, this thesis is aiming at following works:1. The fundamental part of the radar signal processing system and waveforms design and comparison among several ones are introduced first. For the multi-target recognition, the ambiguity functions of related waveforms are given. Based on these theories, the information fusion method and the model of RSN are proposed as the basis of the whole research work.2. Multi-target resolution model is set for the RSN. According to the distribution of the RSN, taken the radar beamforming and incorporated RSs into consideration. Conditions for RSN multitarget resolution are given. The conclusion verifies that for the same targets, the RSN can detect them from different positions and angles, The multi-target resolution of the system is a system with much more strong performance, which is not merely a comparable independent RSs combination. It’s resolution performance overcomes the single RS. Additionally, resolution results of three radar signal waveforms are analyzed and compared.3. The resolution model of the RSN is established. Under the conditions of Path-loss model and White Gaussian Noise(WGN), the RSN fusion center makes decision based on the maximum likelihood(ML) criterion. The results of simulation and comparison for system detection and resolution performance of the RSN model are obtained. The relation among the performance of the radar detection, signal-to-noise ratio(SNR), the number of RS and targets are shown, and the detection of the LFM wave-form is the best.4. A RSN model is constructed for multi-target high resolution. The interconnection between RSN model and mutual angle and position relation of the targets is analyzed. The resolution conditions of multi-targets in time domain for the model are acquired through derivation of the ambiguity functions. Simulation results demonstrate that the recognition of multi-targets, the comparison of different types of radar and targets is given.