In many passive localization applications, the reference waveform of received electromagnetic signals is partly known. The in such scenarios are formulated by modelling relationship between data and known signal parameters interest, as time-difference-of-arrival (TDOA) frequency-difference-of-arrival (FDOA). By exploiting prior information carried signal, negative impact random noise can be sig...

Multiple platform coherent location systems operate by computing the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) among signals received at geographically separated platforms. The bandwidth of the data link is the major bottleneck in the processing. Previously developed data compression methods [1, 2] can not satisfy the compression ratio and the accuracy require...

This paper deals with the 3-D moving source localization using time difference of arrival (TDOA), frequency (FDOA), angle (AOA) and AOA rate measurements, gathered from a set spatially distributed receivers. The TDOA, FDOA, measurement equations were firstly established according to space geometric relationship relative Then an efficient closed-form algorithm for position velocity estimation qu...

To obtain the accurate time difference of arrival (TDOA) and frequency (FDOA) for passive localization in an unmanned aerial vehicle (UAV) swarm, UAV swarm network synchronization is necessary. However, most traditional distributed protocols are based on iteration, which hinders efficiency improvement. High communication costs long convergence times often required large-scale networks. This pap...

Because a primary task of multi-sensor systems is to make estimates based on the data collected and shared throughout the sensor system, it is important to design data compression methods that reduce the volume of data to be shared while causing only minimal degradation of the quality of these estimates. An important aspect not specifically considered previously in compression research for sens...

—This paper derives the performance equation of the differential calibration algorithm using the time differences of arrival (TDOA) and the frequency differences of arrival (FDOA) with calibration sources when the positions and velocities of the receivers have random errors. By comparing the performance with the Cramér-Rao lower bound (CRLB), it proves that the ability of the differential cali...

This paper develops the model of joint phantom track deception and techniques time-difference arrival (TDOA) frequency-difference (FDOA) localization to deceive air defense radar networks under condition that an unmanned aerial vehicle (UAV) swarm has no prior knowledge radars’ precise locations, related performance experiment analysis are presented demonstrate effectiveness proposed method cla...

Technische Fakultät Institut fur Informatik Telecommunications Engineering Tracking a Mobile Receiver using the Unscented Kalman Filter by Joan Bordoy Andreu Indoor localization based on Time Difference of Arrival (TDOA) and Frequency Difference of Arrival (FDOA) has been a promising subject of study the last years. In this thesis, a moving target is tracked by receiving discrete signals from s...