Experimental validation of beamforming techniques for localization of moving target in passive radar

Abstract

We investigate the performance of a Bucci based beamformer design and MUSIC algorithm under a passive radar setup using experimental measurements. A uniformly spaced linearly array of 11 discone antennas was used for the passive radar. The experiment was performed by exploiting the DVB-T broadcasting station as the illuminator of opportunity. In order to suppress the direct reference signal and clutters, the beamforming and MUSIC algorithms have been applied to the range-Doppler processed data; however, challenges remain due to very low SNR. This work proposes spatial smoothing based Bucci algorithm whose angle of arrival estimation performance is comparable to that of the MUSIC algorithm, however, this method does not need the computationally expensive singular value decomposition

Passive Radar Array Processing with Non-Uniform Linear Arrays for Ground Target’s Detection and Localization

“…First stage beams were designed under the condition of the maximally flat response between beams' directions. A more crowded set of beams was used in the second stage for DoA estimation using a spatial smoothing-based Bucci algorithm proposed in [32].…”

Experimental validation of Kalman filter based tracking in passive radar systems

“…In order to localize the target in Cartesian coordinates and enhance the signal to noise ratio, a uniformly spaced linearly array of 11 discone antennas has been used and a spatial smoothing Bucci beamforming has been applied [4]. Once the DoA has been estimated, it has been used as input of the tracking algorithm described in Sec.…”

“…Alternatively, single passive radar with multiple antennas can localize the target using the time delay of arrival estimation and the estimation of the angle of arrival of the reflected signal. This experiment is based on the second approach where target is localized using multiple antenna technology and angle of arrival estimation based on root MUSIC (MUltiple SIgnal Classification) algorithm [1] [2] [3] [4]. In order to track the targets, the bistatic range and bistatic velocity estimated using Doppler shifts are exploited using the Kalman filter.…”

The Impact of Channel Errors in Passive Coherent Location Radar using FM Base Stations

“…These advantages are derived from the lack of the transmitter. The PCL system operates by using transmitters which already exist in use for other purposes such as Global System for Mobile Communications (GSM) [7], Wireless Fidelity (WIFI) [8], Analogue TV, Digital Audio Broadcast (DAB), Digital Video Broadcasting-Terrestrial (DVB-T) [9,10], Digital Video Broadcasting-Satellite (DVB-S) [11], and FM radio [12] instead of a dedicated transmitter. On the other hand, the lack of the transmitter in the PCL system causes drawbacks such as complicated signal processing, not having control over the transmitted signal and continuous synchronization between receiver and transmitter.…”