Dissertation
Dissertation > Industrial Technology > Radio electronics, telecommunications technology > Radar > Radar tracking system

Dim Multi-Targets Detect and Tracking Based on Dynamic Programming

Author KuLiang
Tutor ZhouZhiPing
School Jiangnan University
Course Detection Technology and Automation
Keywords Dim Targets Track-Before-Detect (TBD) Dynamic Programming algorithm (DPA) Multiple Hypothesis Tracking (MHT) Two Stage Approach
CLC TN953
Type Master's thesis
Year 2009
Downloads 258
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In the radar targets detection and tracking process, regarding the long-distance range image which is obtained, the image formation area of the targets is small, and the detected signal is weak, specially under the complex background disturbance, the targets are submerged by the massive noises, that causes the signal-to-noise ratio of the image to be very low, and the targets detection become difficult. Therefore, under the low signal-to-noise ratio condition, the moving dim targets detection question in the sequence images has become the key question which urgently awaits to be solved, exploring and studying the dim targets detection theory as well as how to apply the available detection theory in the dim targets will be still an important topic, which will have the profound significance to the modern warfare as well as the future war. Under the intermediate and senior sea sentiment sea noise jamming background, it is difficult that detecting marine static or the slow movement targets using the pulse Doppler airborne radar, specially such dim targets as the submarine telescope and the air vent. Because the targets do not have the Doppler shift or the targets Doppler shift is quite small, and the background sea clutter still had certain Doppler shift, it is extremely difficult to distinguish the Doppler shift of the targets using the traditional PD technology, so we need to consider other methods to distinguish the dim targets. As a result of the airborne radar approach particularity, we cannot depend upon the methods which purely reduces the sea noise jamming absolute intensity to solve this technical difficult problem, and must enhance the signal-to-noise ratio and reduce the sea clutter false alarm rate, then we can have the solution to the difficult problem that detecting marine static or the slow movement dim targets under the high strength sea clutter background using airborne radar.There are two basic approaches for tracking dim targets as conventional and track-before-detect (TBD). The conventional approach uses sophisticated signal processing and tracking methods to produce observations that, after thresholding, are sent to a separate tracking algorithm. The recently proposed TBD approach combines signal processing and tracking so that detection and track confirmation effectively occur simultaneously. The main work of this paper is as follows:1. It is studied how to apply dynamic programming algorithm, which is an effective track before detect method, in the radar dim targets detection and tracking. This method accumulates the energy in the multi-frame image data along the target trajectories, and chooses a target trajectory whose accumulation value is biggest from all possible trajectories. We can usually consider a trajectory is composed of a series of states, and each state describes the related information of each pot in the trajectory. The trajectory optimization process is also the state sequence optimized process.2. A data association method -- track-oriented algorithm which is ideal for tracking dim targets in clutter is studied. The MHT algorithm can typically extend tracking operation to a false alarm density that is at least 10 times greater than the density at which a nearest neighbor type method can operate.3. According to the content described above, a two stage tracking method is studied. This process will use dynamic Programming algorithm as the first stage to detect likely track segments in the raw data. Then MHT is used as the second stage to link the track segments produced by the first stage and confirm the final track. The ultimate performance against low SNR targets can probably be obtained using this two-stage detection and track confirmation process.

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