KEYWORDS: Signal to noise ratio, Fuzzy logic, Detection and tracking algorithms, Personal digital assistants, Filtering (signal processing), Error analysis, Algorithm development, Surveillance, Defense and security, Data conversion
The problem of multisensor-multitarget tracking is mainly dependent on the data association. In this paper, the fuzzy logic-based single target tracker is extended to the multitarget case. Multitarget scenario incorporating four targets both maneuvering and non-maneuvering in the same surveillance volume is analyzed. The proposed multitarget tracker, also called the Multitarget Tracking - Fuzzy Data Association “MTT-FDA” tracker, employs fuzzy variables capable of resolving the problem of multiple crossing targets. These variables are the rate of change of the target states over a sliding window. It has been observed through simulations that a window size of five time scans is sufficient to yield acceptable results. Moreover, the proposed tracker was exercised against the realistic multitarget data set. The results reveal that the proposed fuzzy tracker yields superior performance compared to other existing tracking schemes.
The research in multitarget tracking has mainly focused on the development and implementation of efficient data association algorithms with acceptable performance. The Viterbi Data Association (VDA) algorithm has proven to have low computation cost and hence a good candidate for the extension to multiple target tracking case. In this paper, the VDA is implemented for tracking both the single and multiple maneuvering targets in clutter. The track initiator and the adaptive sliding window techniques are used so that the VDA can maintain a lock on the track. The performance of the algorithm is assessed via Mote-Carlo simulations. The computation complexity analysis reveals that the VDA is computationally more efficient over the known tracking techniques.
KEYWORDS: Missiles, Signal to noise ratio, Fuzzy logic, Aerodynamics, Control systems, Error analysis, Data modeling, Kinematics, Monte Carlo methods, Systems modeling
The research conducted in the last decade in missile design has mainly focused in the area of guidance and control. Many researchers have designed interceptors with high performance; namely: ranging from the classical control to the knowledge based techniques. The homing guided missile flight simulation testbed has been developed and tested against different control systems. The missile aerodynamic model has been simulated based on NASA reports and the output aerodynamic coefficients have been compared and justified by the wind tunnel tests as well. The other missile modules have been simulated and compared to the real missile modules in terms of input/output experimental results. The guidance and control system has yield excellent performance against incoming and outgoing maneuvering targets falling within the missile's destruction zone. However, all the test scenarios assumed that the target information from the missile seeker (tracker) is exact and obtained from the observations without any major difficulty. In the case of high density clutter and false alarms as well as the low signal-to-noise-ratio (SNR) which may be due to the existence of flair, decoy or any other counter measure, the tracker accuracy plays an important role in the over all engagement scenario. In this paper, a fuzzy logic-based technique has been employed to improve the performance of the missile seeker at high density clutter and low SNR. The Interacting Multiple Model Fuzzy Data Association (IMM-FDA) has been employed to improve the missile-target intercept accuracy.
KEYWORDS: Signal to noise ratio, Fuzzy logic, Personal digital assistants, Target detection, Filtering (signal processing), Detection and tracking algorithms, Motion models, Data modeling, Signal detection, Switching
The Interacting Multiple Model (IMM) estimator is a suboptimal hybrid filter that has been shown to be one of the most cost-effective hybrid state estimation schemes. The algorithm has the ability to estimate the state of a dynamic system with several modes which can switch from one mode to another. It is also considered to be the best compromise between the complexity and the performance. It is mainly used for tracking highly maneuvering targets in the presence of clutter by invoking the Probabilistic Data Association (PDA) in the estimator structure, also called IMM-PDA. Recently, it has been shown that the PDA technique does not perform well when tracking targets at low signal to noise ratios (SNR). An alternative technique to data association is the Fuzzy Data Association (FDA) which has the ability to track targets in clutter and in a low SNR environment. In this paper, an IMM-FDA technique is proposed for tracking highly maneuvering targets in clutter and in a low SNR environment. Simulations have been conducted to compare the performance of the proposed approach with that of the IMM-PDA. A typical scenario for a highly maneuvering target is considered as a tracking example. The simulation results reveal that both the trackers perform well when tracking the maneuvering target at high SNR. At low SNR, only the IMM-FDA is able to track the target accurately.
In maritime operations, target tracking and localization, also called target motion analysis (TMA), is an important issue. If an active sensor is used, the tracking process will be observable since we can predict the target range and bearing without any difficulty. The major disadvantage of using the active sources is that the enemy's targets can easily detect the ship position. Thus, tracking using active sources become a risky proposition. The alternative is to use passive tracking, but in this case the tracking process will be unobservable because we can only measure the target bearing. The range can be estimated via triangularization by using at least two platforms. Another method is to try to find the range using a geometrical approach to have at least one accurate range and then we can use it to construct the track under some assumptions. In this paper, a geometrical approach to bearing-only tracking is introduced. The target range is derived using few bearing measurements. Several own ship-target geometries have been set up for this purpose. To compute the target range, it is required that the own ship execute an admissible maneuver. The geometrical approach presented provides an acceptable performance and can be used for a short time period in the tracking process to provide a reasonable estimate of the range and then the tracker can use this range to generate the target track and hence reduce the bias.
KEYWORDS: Fuzzy logic, Target detection, Signal to noise ratio, Filtering (signal processing), Personal digital assistants, Signal detection, Electronic filtering, Detection and tracking algorithms, Environmental sensing, Logic
Most of the real world engineering problems are imprecise and they carry a certain degree of fuzziness in the description of their nature. Fuzzy logic is a design methodology that can be used to solve real life problems. It has the advantage of lower development costs, superior features, and better end product performance. Fuzzy logic makes it possible to describe complex systems using expert experience and knowledge in English-like rules, which are easy to learn and use, even by non-experts. Fuzzy technique does not require system modeling or complex mathematical equations. The design methodology is to first understand and characterize the system behavior by using our basic knowledge and experience and then design the algorithm using the fuzzy rules that describe the relationship between its input and output. This is done by debugging the design through simulations and if the performance is not satisfactory we only need to modify or add some fuzzy rules. There exists considerable literature on target tracking based on the Kalman filtering and probabilistic data association (PDA) techniques. A few of these techniques can yield acceptable results in a high-density clutter environment due to the complexity of combined target and measurement to track association or due to the simplification assumed in these techniques. This paper presents the use of fuzzy association rules involved in data association of target measurements under a high-density clutter. The fuzzy tracker is used to track a target and its performance is compared with a standard PDA filter for various signal-to-noise ratios (SNR).
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