A closed-form solution for target localization based on the realistic distance-dependent noises in Illuminator of opportunity passive radar and the reduction method of the bias which exists in the two-stage weighted least squares (2SWLS) method is proposed. 2SWLS is a classic method for time-of-arrival (TOA) and frequency-of-arrival (FOA) localization problem and has a couple of improved solutions over the years. The 2SWLS and its improved solutions have great localization performances in their established location scenarios on the basis of two approximations that setting the noise to a constant and ignoring the high-order terms of TOA and FOA measurement noises. It is these two approximations that lead to a sub-optimal solution with bias. The bias of 2SWLS has a significant influence on the target localization in Illuminator of opportunity passive radar that has lower measurement accuracy and higher noises than active radar. Therefore, this paper starts by taking into consideration of the realistic distance-dependent characteristics of TOA/-FOA noises and improving 2SWLS method. Then, the bias of the improved 2SWLS method is analyzed and a bias-reduced solution based on weighted least squares (WLS) is developed. Numerical simulations demonstrate that, compared to the existing improved solutions of the 2SWLS, the proposed method effectively reduces the bias and achieves higher localization accuracy.

Due to increasing growth of air traffic, it is very important to have a reliable air traffic control system. Usually secondary surveillance radar systems are employed for this task. In this paper, a new approach is presented to identify interrogators location of this system. The proposed method works passively and uses just a single receiver. This goal has been reached using angle and time difference of arrival information. How to determine the desired angle and calculate the time difference of arrival from the received data is described. knowing this information, a closed-form solution in polar coordinate is presented and its sensitivity is measured. Then a method is proposed based on maximum likelihood estimation of the target location. Afterward angle and time difference of arrival equations are linearized and then weighted least squares estimation is achieved. The suggested approach is evaluated on real and practical information and the results have finally been reported.

passive target localization has many applications in electronic warfare and passive defense. TDOA is the most accurate method in target localization. Following this method, one of the receivers is assigned as reference receiver and time difference of arrival between other receivers and reference receiver is measured. The target location is estimated by processing of these TDOA. The CTLS is one of TDOA based algorithm that has high accuracy and needs suitable initialization. In this paper, multi reference CTLS algorithm is proposed. CTLS algorithm accuracy was improved when multi reference receiver are considered instead of one reference receiver. Simulation results show that the proposed algorithm in different SNR, keep its improvement just with little increase of time processing and better performance compared to CTLS algorithm has been obtained.

This paper proposes a novel scheme for multi-static passive radar processing, based on soft-input soft-output processing and Bayesian sparse estimation. In this scheme, each receiver estimates the probability of target presence based on its received signal and the prior information received from a central processor. The resulting posterior target probabilities are transmitted to the central processor, where they are combined, to be sent back to the receiver nodes or used for decision making. The performance of this iterative Bayesian algorithm comes close to the optimal Multi-Input Multi-Output (MIMO) radar joint processing, although its complexity and throughput are much less than MIMO radar.Also, this architecture provides a tradeoff between bandwidth and performance of the system. The Bayesian target detection algorithm utilized in the receivers is an iterative sparse estimation algorithm named Approximate Message Passing (AMP), adapted to SISO processing for passive radar. This algorithm is similar to the state of the art greedy sparse estimation algorithms, but its performance is asymptotically equivalent to the more complex l1-optimization. AMP is rewritten in this paper in a new form, which could be used with MMSE initial filtering with reduced computational complexity. Simulations show that if the proposed architecture and algorithm are used in conjunction with LMMSE initial estimation, results comparable to jointly processed basis pursuit denoising are achieved. Moreover, unlike CoSaMP, this algorithm does not rely on an initial estimate of the number of targets.

In this paper, we deal with the problem of clutter and direct signal (C& DS) cancelation in the target detection of TV-based passive radars. We first consider the target detection using the conventional FFT method. We see that for increasing the maximum range of passive radar, we must cancel the C& DS from the received signal. Hence, we investigate some important methods for C& DS cancelation in the TV-based passive radars using some evaluation criteria such as the ability for cancelation of undesired echoes, the effect on the target peak, detection performance, and the computational complexity. Afterward, we propose a new algorithm for C& DS cancelation based on the adaptive filter bank. Our investigations show that the proposed algorithm with much less complexity, behaves close to the ECA.

In this research a mathematical model for surface radar sites’ location and a combination methodology for its resolution are presented. Hence after expressing the related conceptions, the goals and radar sites location method, mathematical model for radar sites location is expressed. Then a two-step method for solving this problem is offered. At the first step, the criteria parameters for selecting radar sites’ location based on passive and active defense are identified, classified, scored and prioritized. Since these kinds of problems are NP-hard, simulated annealing algorithm for solving this new mathematical model has been used. In this method the total score for each candidate location determines the position priority for radar network. So all of the possible states for the radar network are survived by stimulated annealing algorithm. Finally, a radar sites’ location problem in the Persian Gulf beaches using presented simulated annealing algorithm with hypothesis data has been resolved.

Multi-transmitter multi-receiver passive radar, which locates target in the surveillance area by the reflected signals of the available opportunistic transmitter from the target, is of interest in many applications. In this paper, we investigate different signal processing scenarios in multi-transmitter multi-receiver passive radar. These scenarios include decentralized processing of reference and surveillance signals, decentralized processing of surveillance signals, and centralized processing of surveillance signals that have different advantages, disadvantages, and requirements. A variety of possible measurements including TDOA, GROA, AOA and their combinations are presented under different scenarios. The Cramer Rao lower band (CRLB) is presented for different signal processing scenarios for the error of the target localization. The efficiency of the target localization for different signal processing scenarios and types of measurements has been investigated by the CRLB. As shown in the simulation results, the combined use of the measurements is always better than their single use. Also centralized and decentralized processing of surveillance signals, by arranging the receiver sensors in the far distances, can have better efficiency than close distance arrangements.

The present study aimed to design and strategy in the field of passive defense radar that conducted in accordance with unbalanced threats. Because the radar is main instruments in the field of air defense command and control thus it is important to air defense power of countries. This paper is the practical studies. a study sample are 37 of experts, and academics in the fields of air defense radar and passive defense. Data were collected through library resources and questionnaire. The questionnaire was adjusted in three stages: Verification of components and features; Review and ranking the strengths, weaknesses, opportunities and threats in the field of passive defense radar and Determine its validity by several members of the High Command of Air Defense as an expert and elite society. Reliability of this paper done by Cronbach's alpha (82.0). Data were analyzed using descriptive statistics then the evaluation matrix, each of the internal and external factors of passive defense in the field of radar been recognized in accordance with asymmetric threats. Research suggests that analyzing the Armed Forces of the Islamic Republic of Iran in the field of passive defense in radar, located in WT positions that should use a defensive strategy. Finally, four main strategies for developing a strategic plan in the field of passive defense radar in accordance with unbalanced threat has been identified and prioritized.

This paper addresses the signal processing principles in passive bistatic radar (PBR) systems. In this case, the detection problem in passive radar systems based on FM radio signals is investigated in the presence of system noise, clutter/multipath, direct signal and interfering target signals. To this light, two types of detectors are studied. In the first one, which is based on intuitive sense and does not have any optimum claim, we examine two detectors. In the second type detector, which is based on detection theory, the detection problem is solved with optimum property out of invariant tests. For the first time, in this paper, the performance of above detectors based on detection probability and false alarm rate probability have been simultaneously compared. This makes it possible to find the advantages and disadvantages of two investigated detectors.

This paper presents a new method of clean processing for cancelling direct signal from the reference channel using Compressed Sensing (CS) in a Multistatic passive synthetic aperture radar (MPSAR) based on DVB-T signal, whose opportunity transmitters are stationary and receiver is moving. This paper develops the linear system model of MPSAR in presence of the direct signal interference and then proposes an CS based algorithm to cancel it. The direct signal amplitude is complex in extractive model. The simulation results indicate that the proposed algorithm (CS) is effective for direct signal cancellation.