Problem Of Passive Detection Research Articles

О поиске источников шума группой взаимодействующих АНПА с применением генетического алгоритма

Marine unmanned systems are increasingly used in tasks related to search and observation missions. Protection of water areas, survey and inspection operations, tracking of marine animals are examples of such missions. Most of these tasks can be solved more efficiently by use a group of interacting marine drones, compared to single vehicle. The article considers the problem of passive detection and localization of noise objects in a given water area by use a group of autonomous underwater vehicles (AUV). It is assumed that antennas of scalar vector receivers are installed on board the AUV to detect and determine the direction to the noise source. Some ways of organizing the group work of such AUV are considered. A centralized version is investigated, when the collected current information from all AUV is transmitted to one AUV leader. On the base of received information processing, AUV leader forms a group work plan, including the motion parameters for all AUV, to detect and determine the location of noise sources. An approach based on the use of a genetic algorithm is considered, and several versions of its implementation are investigated. The results of model experiments are presented, which demonstrate the efficiency of the proposed algorithms.

Acoustic fields of unmanned aerial vehicles in the tasks of passive detection

The increasingly widespread use of unmanned aerial vehicles (UAVs) requires improved methods of their detection. In some cases, this is only possible by analyzing the physical fields created by the UAV. This work is dedicated to the study of the UAV’s acoustic field as applied to the problem of passive detection. In the laboratory, the acoustic fields of the most popular quadcopters were studied, as well as the properties of individual propellers of various designs. The influence of blade defects on the resulting spectral portrait was analyzed. Based on the results of numerical simulations in the COMSOL Multiphysics software package, directional patterns and pressure variations caused by a rotating propeller are obtained. A neural network has been trained to analyze the kepstrum coefficients calculated from acoustic records. The neural network allows monitoring and recognizing the presence of a quadrocopter in an area of interest, taking into account natural and anthropogenic noises. Field experiments carried out in urban conditions made it possible to estimate the range of possible passive detection of an unmanned aerial vehicle. [This work was financially supported by the Russian Foundation for Basic Research (Project No. 19-29-06062).]

Two-Channel Passive Detection of Cyclostationary Signals

This paper addresses a two-channel passive detection problem exploiting cyclostationarity. Given a reference channel (RC) and a surveillance channel (SC), the goal is to detect a target echo present at the surveillance array transmitted by an illuminator of opportunity equipped with multiple antennas. Since common transmission signals are cyclostationary, we exploit this information at the detector. Specifically, we derive an asymptotic generalized likelihood ratio test (GLRT) to detect the presence of a cyclostationary signal at the SC given observations from RC and SC. This detector tests for different covariance structures. Simulation results show good performance of the proposed detector compared to competing techniques that do not exploit cyclostationarity.

Target detection for a kind of troposcatter over‐the‐horizon passive radar based on channel fading information

The troposcatter over-the-horizon (OTH) passive radar plays an important role in the beyond-line-of-sight surveillance, for its high propagation reliability and low probability of interception. However, it has two major limitations, namely, large propagation losses and multipath scattering fading. Since the captured signals are non-stationary with low signal-to-noise ratio, high antenna gain is indispensable, which results in narrow beamwidth. To deal with the contradiction between narrow beamwidth and real-time wide spatial coverage, array receiving is promising. Then, the primary problem is the array signal detection under troposcatter fading correlations. Based on recent troposcatter fading model, this study addresses this passive detection problem in three cases: (i) the spatial–temporal correlation is known, and a Neyman–Pearson detector is proposed as benchmark; (ii) uncertain statistics exist in the spatial–temporal correlation, and a generalised likelihood ratio test is adopted to overcome this uncertainty; (iii) the fading correlation is totally unknown, and a spatial–temporal weighted covariance-based detector is proposed. The performances of the proposed detectors are verified by Monte-Carlo simulations and experiments in a linear array, which is instructive for this kind of passive radar design in practical. Comparisons with existing detectors and the benchmark confirm the feasibility and effectiveness for troposcatter OTH passive radar.

Passive Detection of Correlated Subspace Signals in Two MIMO Channels

In this paper, we consider a two-channel multiple-input multiple-output passive detection problem, in which there is a surveillance array and a reference array. The reference array is known to carry a linear combination of broadband noise and a subspace signal of known dimension, but unknown basis. The question is whether the surveillance channel carries a linear combination of broadband noise and a subspace signal of the same dimension, but unknown basis, which is correlated with the subspace signal in the reference channel . We consider a second-order detection problem where these subspace signals are structured by an unknown, but common, $p$ -dimensional random vector of symbols transmitted from sources of opportunity, and then received through unknown $M\times p$ matrices at each of the $M$ -element arrays. The noises in each channel have spatial correlation models ranging from arbitrarily correlated to independent with identical variances. We provide a unified framework to derive the generalized likelihood ratio test for these different noise models. In the most general case of arbitrary noise covariance matrices, the test statistic is a monotone function of canonical correlations between the reference and surveillance channels.

Broadband target beam-space transformation in generalized likelihood ratio test using acoustic vector sensor array

Aiming at the problem of passive detection of broadband sources in underwater acoustic vector signal processing, a novel detection algorithm based on beam-space transformation is proposed. The principle of spatial spectrum detection with human eyes is employed for reflerence, and the generalized likelihood ratio test (GLRT) is applied to the beam-space. First, the design criterion of beam-space transformation matrix is studied for the compreflensive consideration of the environment of multiple targets and the characteristic of vector ambient noise field, so that the analytical solution is obtained. Second, assuming that the number of beams not containing the target signal is given, the probability density function (PDF) model of beam-space data is constructed, and the new GLR test is made by calculating the maximum likelihood estimate of the unknown variables in PDF. Finally, the information of theoretical criterion is adopted in order to estimate the number of beams not containing target signals. The processing gain and the threshold value of this test statistics are also discussed, and the specific implement is explained in detail. Theoretical analysis and simulation results show that under the complex conditions of strong target interference and ambient noise with undulated and time-variant power spectrum, the proposed algorithm can give the processing result with higher gain and detection threshold at constant false alarm rate (CFAR); the results of lake experiment further prove the favorable and robust detection performance.

Two Target Detection Algorithms for Passive Multistatic Radar

This paper considers the problem of passive detection with a multistatic radar system involving a noncooperative illuminator of opportunity (IO) and multiple receive platforms. An unknown source signal is transmitted by the IO, which illuminates a target of interest. These receive platforms are geographically dispersed, and collect independent target echoes due to the illumination by the same IO. We consider a generalized canonical correlation (GCC) detector for passive detection which requires the knowledge of the noise power. We derive closed-form expressions for the probabilities of false alarm and detection of this detector. For the case where the noise power is unknown, we propose a generalized likelihood ratio test (GLRT) detector to deal with the passive detection problem. Moreover, a closed-form expression for the probability of false alarm of this GLRT detector is given, which shows that the proposed GLRT detector exhibits a constant false alarm rate property with respect to the noise power. Numerical simulations demonstrate that the proposed GLRT detector generally outperforms the generalized coherence detector, a previous popular passive detector that neither requires the knowledge of the noise power. In addition, the GLRT also outperforms the GCC detector when the latter has an uncertainty in its knowledge of the noise power.

Detection of Surface Ships From Interception of Cyclostationary Signature With the Cyclic Modulation Coherence

This paper addresses the problem of passive detection of surface ships from radiated propeller noise in the far field. This is traditionally accomplished by means of envelope analysis, a largely empirical technique. The first contribution of the paper is to give a formal justification why this approach is sound based on the cyclostationary modeling of propeller noise. Pursuing along similar lines, the paper proposes a new statistical test based on the recently introduced cyclic modulation coherence (CMC), which is close to optimal in detecting cyclostationary noise, while at the same time being easy and extremely fast to compute. Detection capability is thoroughly investigated as a function of the blade pass frequency and other parameter settings. Finally, the cyclostationarity framework makes possible the proposal of a closed-form statistical threshold that opens the way to automatic detection.

Ray caustics and passive detection solutions for boundary reflections in a constant-gradient medium

For a bottomless medium characterized by a positive constant gradient, the multiple reflection problem is treated by analysis of the following: (1) The Simulation Problem: Given the relative coordinates x and y between source and receiver, determine the orientations of those rays which succeed in impinging upon the receiver by use of the acquiring-ray approach. The existence condition for real roots of the acquiring-ray cubic and quartic equations treated herein facilitate the determination of the caustic equations. When the condition is imposed that the discriminant of the cubic or quartic equation be zero valued, the caustic equation emerges as the boundary line among which repeated roots occur. For the single reflection case, a cubic equation must be solved and the associated caustic curve has the shape of a cusped semicubical parabola. For n reflections (n ⩾ 2), a quartic equation must be treated and the two caustics of the nth order are derived from the discriminants of the quadratic factors composing the quartic equation. Explicit closed-form solutions for the caustics are obtained by use of reciprocity and reduction-to-single-reflection-type arguments. The mathematical form and physical significance of the caustics is discussed. (2) The Passive Detection Problem: Given only the ray orientations at the receiver, determine the vertical and horizontal distances between source and receiver. For both problems, no restrictions are imposed on the source and receiver depths.