Target Localization by Resolving the Time Synchronization Problem in Bistatic Radar Systems Using Space Fast-Time Adaptive Processor

Abstract

The proposed technique allows the radar receiver to accurately estimate the range of a large number of targets using a transmitter of opportunity as long as the location of the transmitter is known. The technique does not depend on the use of communication satellites or GPS systems, instead it relies on the availability of the direct transmit copy of the signal from the transmitter and the reflected paths off the various targets. An array-based space-fast time adaptive processor is implemented in order to estimate the path difference between the direct signal and the delayed signal, which bounces off the target. This procedure allows us to estimate the target distance as well as bearing.

A SimpleMethod to Derive the Bistatic Tracking Radar System Formulas

“…The simulation results for such assumed conditions of the target are listed in table (1). The flow chart shown in figure (6) illustrates the steps to compute the position of the transmitter antenna relative to the position of the receiver antenna,…”

“…Derivation of equations (6) and 7is given in appendix C. The direction of transmitter antenna (ψ t ) can be calculated in the same manner as used to derive the receiver antenna direction formula, which is given in appendix A. This direction is given by the following formula:…”

“…The implementation of the bistatic radar is more complex than the monostatic radar because it needs synchronization for time, frequency, and antenna positioning [5]. Many researches have been made to solve these problems such as in references [6,7,8,9]. In addition, the equation of bistatic radar is more complex than that of monostatic radar.…”

A RSSI-based parameter tracking strategy for constrained position localization

“…Among a number of channel models proposed for outdoor and indoor environments (Nakagami, Rayleigh, Ricean, etc. ), the most popular channel model for RSSI-based localization, thanks to its simplicity, is the lognormal shadowing path loss model [30,31], which expresses the following relation between the received power and the transmitter-receiver distance:…”

“…In the measurement, to acquire a large number of RSSI values in each distance, we give a same distance value between each access point and the mobile point, for example 1 m. Then in the process of measurement, the mobile point is changed for 30 directions but its distance with the three APs is not changed. So, the mobile point receives 30 Based on the measured RSSI data, the median RSSI is calculated for one distance. Figure 4 presents the measured median RSSI as function of the distance.…”