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Localization algorithms are traditionally developed to minimize the impact of observation errors on accurate positioning by considering the errors in observations obtained from the target. When dealing with a moving sensor, navigation systems provide reports on the sensor's locations. Consequently, the localization methods in this approach need to be modified to incorporate the navigation errors along with the erroneous target observations in the equations, with the aim of reducing the impact of these errors on positioning accuracy. This paper focuses on utilizing passive positioning methods with moving sensors and presents an analysis and design of a method to enhance the speed and accuracy of positioning algorithms, while also updating the error estimates in observations and navigation reports. Simulation results demonstrate that the single-stage generalized least squares algorithm consistently yields the most accurate results across all scenarios and is suitable for real-world conditions. Additionally, an algorithm based on adaptive filters has been devised to expedite convergence speed. Moreover, the factors influencing convergence speed have been analyzed, and a solution to enhance convergence speed has been proposed. By examining Kramer Rao's bound in various methods, a novel framework has been developed. In this article, the intersection and rotation algorithm is employed to combine orientation-based and time-based energy transmission methods. These algorithms are characterized by their high accuracy, low computational overhead, and resilience to measurement noise. Simulation-based evaluations have been conducted, demonstrating the superior performance of the proposed method compared to existing approaches in terms of quality and effectiveness.

One of the points that can be deduced from the study of common methods and techniques in electronic warfare is that none of these methods is considered absolute winners and the holder can’t consider himself the undisputed winner of this field because there is more or less the opposite of every technique. Using a method or tool in a situation can be very effective, but it becomes a weakness when a competitor changes the method or tool. Therefore, in this battle, the correct and timely use of any technique and with full knowledge of the opponent and in accordance with the actions performed by him can be considered a factor of success and use all useful tools in this field. One of the useful tools in the field of strategic decision analysis is the game theory. With the help of this mathematical tool, the decision-making process between two or more decision-makers can be examined and the results can be analyzed. It is also possible to observe the effect of various parameters involved in the result of the problem and plan the result in the desired direction. In this paper, the selection of the best response in different stages of the conflict to solve different problems has been achieved. The main purpose is to provide a new approach to adopt a strategy, select radar technique, destructive response in case of incomplete information from each. The second goal is to use mathematical and algorithmic methods for better performance in the functionality of the parties.

In distance measurement with the help of delay of pulse reception time, the target distance is determined by the time interval between the emission of a pulse and its echo reception. In elementary radars, measurements were made on the screen distance trace. In advanced analog radars, measurements are made by sequential opening of distance windows. Digital radars do the same thing by intermittently sampling the receiver output, converting samples to numbers, and storing these numbers in a bank of distance cells. The distance whose return time is equal to the pulse transmission period is called the maximum unambiguous distance. The solution to the ambiguity problem depends on the presence of ambiguities and the risk of ambiguity for the system. In this article, we look at a type of ambiguity called "ghosts" and look at how to remove it. Finally, we will briefly describe how to measure distance while tracking a single target. If the PRF can be considered so low that it is required from the maximum distance, the problem can be solved by eliminating returns related to farther goals. This can be easily done using the jump rate (Jitter). If higher PRFs are needed, then ambiguity is no longer appropriate, but we must clear up the ambiguities. This can be accomplished by successively switching the PRF between two or more consecutive values, and measuring changes in apparent boards. In this technique, if two targets are revealed simultaneously, each of them has two apparent distances, and the wrong choice of the pair of apparent locations of each target leads to a kind of error called a ghost. Ghosts can be removed by using additional PRFs. Using more than one PRF, in addition to adding complexity, also reduces the maximum radar range. Therefore, in choosing the optimal number of PRFs, a compromise must be made between these costs and the costs associated with occasional encounters with unresolved ambiguities and ghosts.