Pengolahan Sinyal Radar Pasif Berdasarkan Electronic Support Measure Dengan Metoda Time Difference of Arrival : Signal Processing of Passive Radar Based Electronic Support Measure With Time Difference of Arrival Method

Radar pasif merupakan peralatan elektronika yang menerima semua gelombang elektromagnetik yang dipancarkan oleh target, dan tidak memancarkan gelombang elektromagnetik. Prinsip radar pasif terdiri dari tiga peralatan penerima (receiver) pada suatu jarak tertentu, dengan menggunakan metode Time Difference of Arrival (TDOA). Metode tersebut digunakan untuk menentukan posisi, jarak, kecepatan, arah sasaran yang terdeteksi. Agar dapat mengidentifikasi sinyal terdeteksi, maka dibutuhkan sebuah processor. Kemudian hasil dari identifikasi sinyal yang telah terdeteksi digunakan untuk menentukan jenis ancaman yang mungkin ditimbulkan, sehingga diperoleh antisipasi untuk mengatasinya. Penelitian ini merupakan implementasi radar pasif untuk mengidentifikasi sinyal terdeteksi yang dipandu dengan sinyal radio frequency (RF) hingga ke display. Pada penelitian ini dibuat prototipe objek yang akan dijadikan media target dan tampilan display dalam bentuk tiga dimensi, dengan relasi geolokasi dan perhitungan geolokasi yang diinginkan dengan jarak maksimal 10 m. Skenario pengujian dilakukan dengan merubah jarak, interval waktu pengambilan dan melihat kesalahan selisih jarak yang diperoleh. Pada penelitian ini, dilakukan pengukuran parameter jarak antara objek dan penerima dari jarak 1 m hingga 10 m, dengan tujuan mengetahui performansi kinerja sistem, dan didapatkan hasil terbaik pada jarak 10 m karena rentang koordinat yang di dapat semakin tepat. Adapun pengujian parameter menggunakan TDOA untuk mendapatkan posisi koordinat dari objek dan stasiun mendapatkan persentase kesalahan selisih jarak sebesar 8,136%. Sistem yang telah dibuat mampu bekerja sesuai pada jarak 10 m. Rentang interval waktu dari pengambilan sistem ini sebesar 0,5 detik – 2,5 detik. Kata Kunci : Radar Pasif, Electronic Support Measure (ESM), Time Difference of Arrival (TDOA

Experimental Measurement of Time Difference Of Arrival

International audienceIn this paper is described an experimental passive localization system based on SDR (Software Defined Radio) components. This system is designed to measure Time Differences of Arrival (TDOA) of radar pulses between two platforms. For a TDOA system, time error between the two receivers must be kept very low, which requires a very accurate way to synchronize the time bases. In this purpose, a custom offline synchronization method is proposed. The overall performances of the system are analyzed. In a small scale outdoor experiment, it has been shown to perform TDOA measurements accurately. The performances measured during this experiment are then extrapolated to a more realistic electronic warfare scenario

Source localization via time difference of arrival

Accurate localization of a signal source, based on the signals collected by a number of receiving sensors deployed in the source surrounding area is a problem of interest in various fields. This dissertation aims at exploring different techniques to improve the localization accuracy of non-cooperative sources, i.e., sources for which the specific transmitted symbols and the time of the transmitted signal are unknown to the receiving sensors. With the localization of non-cooperative sources, time difference of arrival (TDOA) of the signals received at pairs of sensors is typically employed. A two-stage localization method in multipath environments is proposed. During the first stage, TDOA of the signals received at pairs of sensors is estimated. In the second stage, the actual location is computed from the TDOA estimates. This later stage is referred to as hyperbolic localization and it generally involves a non-convex optimization. For the first stage, a TDOA estimation method that exploits the sparsity of multipath channels is proposed. This is formulated as an f1-regularization problem, where the f1-norm is used as channel sparsity constraint. For the second stage, three methods are proposed to offer high accuracy at different computational costs. The first method takes a semi-definite relaxation (SDR) approach to relax the hyperbolic localization to a convex optimization. The second method follows a linearized formulation of the problem and seeks a biased estimate of improved accuracy. A third method is proposed to exploit the source sparsity. With this, the hyperbolic localization is formulated as an an f1-regularization problem, where the f1-norm is used as source sparsity constraint. The proposed methods compare favorably to other existing methods, each of them having its own advantages. The SDR method has the advantage of simplicity and low computational cost. The second method may perform better than the SDR approach in some situations, but at the price of higher computational cost. The l1-regularization may outperform the first two methods, but is sensitive to the choice of a regularization parameter. The proposed two-stage localization approach is shown to deliver higher accuracy and robustness to noise, compared to existing TDOA localization methods. A single-stage source localization method is explored. The approach is coherent in the sense that, in addition to the TDOA information, it utilizes the relative carrier phases of the received signals among pairs of sensors. A location estimator is constructed based on a maximum likelihood metric. The potential of accuracy improvement by the coherent approach is shown through the Cramer Rao lower bound (CRB). However, the technique has to contend with high peak sidelobes in the localization metric, especially at low signal-to-noise ratio (SNR). Employing a small antenna array at each sensor is shown to lower the sidelobes level in the localization metric. Finally, the performance of time delay and amplitude estimation from samples of the received signal taken at rates lower than the conventional Nyquist rate is evaluated. To this end, a CRB is developed and its variation with system parameters is analyzed. It is shown that while with noiseless low rate sampling there is no estimation accuracy loss compared to Nyquist sampling, in the presence of additive noise the performance degrades significantly. However, increasing the low sampling rate by a small factor leads to significant performance improvement, especially for time delay estimation

Smart Passive Localization Using Time Difference of Arrival

A smart passive localization system using time difference of arrival (TDoA) measurements is designed and analyzed with the goal of providing the position information for the construction of frequency allocation maps

Emitter Location Finding using Particle Swarm Optimization

Using several spatially separated receivers, nowadays positioning techniques, which are implemented to determine the location of the transmitter, are often required for several important disciplines such as military, security, medical, and commercial applications. In this study, localization is carried out by particle swarm optimization using time difference of arrival. In order to increase the positioning accuracy, time difference of arrival averaging based two new methods are proposed. Results are compared with classical algorithms and Cramer-Rao lower bound which is the theoretical limit of the estimation error

The Time Difference of Arrival Estimation of Wi-Fi Signals

The papers deals with a modeling of a Time- Difference of Arrival system for a subscriber station localization, based on the 802.11 standard wireless network. In the case of severe multipath effects the standard TDOA estimation methods, based on correlation of signals, received by conveniently displaced receiving stations show large errors. Thus, a new algorithm is proposed using received signals decomposition to a set of delayed replicas. This represents a linear estimation of reflected signals amplitudes. The described method leads to a better estimation of time differences of the signals, propagating on the direct paths between the emitter and the receiving stations

Observed time difference of arrival based position estimation for LTE systems: simulation framework and performance evaluation

Precise user equipment (UE) location is paramount for the reliable operation of location-based services provided by mobile network operators and other emerging applications. In this paper, the Long Term Evolution (LTE) network positioning performance based on mobile assist Observed Time Difference of Arrival (OTDoA) method is considered. The received signal time difference (RSTD) measurements are estimated by the UE using dedicated position reference signal (PRS) transmitted in the downlink frame where the reported time measurements are used by the network for location calculation. A simulation framework for the position estimation in LTE networks is presented where the LTE downlink communication link is implemented. The correlation-based method for the time of arrival measurement is used for the implementation of OTDoA. The simulation framework provides different configurations and adjustments for the system and network parameters for evaluating the performance of LTE positioning using OTDoA over multipath fading channels. Different simulation scenarios are conducted to identify the influence of various parameters of LTE system and positioning procedure setup on the positioning accuracy. Simulation results demonstrated that the positioning accuracy is highly affected by the channel fading condition where the accuracy of time of arrival measurements is deteriorated in severe fading environments; however, the positioning accuracy can be significantly improved by increasing the positioning sequences involved in the estimation process either in the frequency domain or in the time domain

On the effect of SNR and superdirective beamforming in speaker diarisation in meetings

This paper examines the effect of sensor performance on speaker diarisation in meetings and investigates the use of more advanced beamforming techniques, beyond the typically employed delay-sum beamformer, for mitigating the effects of poorer sensor performance. We present superdirective beamforming and investigate how different time difference of arrival (TDOA) smoothing and beamforming techniques influence the performance of state-of-the-art diarisation systems. We produced and transcribed a new corpus of meetings recorded in the instrumented meeting room using a high SNR analogue and a newly developed low SNR digital MEMS microphone array (DMMA.2). This research demonstrates that TDOA smoothing has a significant effect on the diarisation error rate and that simple noise reduction and beamforming schemes suffice to overcome audio signal degradation due to the lower SNR of modern MEMS microphones. Index Terms — Speaker diarisation in meetings, digital MEMS microphone array, time difference of arrival (TDOA), superdirective beamforming 1

Indoor Positioning Using Acoustic Pseudo-Noise Based Time Difference of Arrival

The Global Positioning System (GPS) provides good precision on a global scale, but is not suitable for indoor applications. Indoor positioning systems (IPS) aim to provide high precision position information in an indoor environment. IPS has huge market opportunity with a growing number of commercial and consumer applications especially as Internet of Things (IoT) develops. This paper studies an IPS approach using audible sound and pseudo-noise (PN) based time difference of arrival (TDoA). The system’s infrastructure consists of synchronized speakers. The object to be located, or receiver, extracts TDoA information and uses multilateration to calculate its position. The proposed IPS utilizes sound waves since they travel much slower compared to electromagnetic waves, allowing for easier measurements. Additionally, the audible spectrum has a large availability of low directivity speakers and microphones allowing for a large coverage area compared to highly directive ultrasonic transceivers. This paper experimentally evaluates the feasibility of the proposed IPS