## 1 Introduction  
Passive radar technology is being extensively developed to foresee and prevent the multiple threats that modern society faces. In recent years, the improvement in computing capacity and the availability of new technological solutions have increased the interest in Passive Radar Systems (PRSs) as an alternative option to active radars. PRSs present many advantages with respect to active ones: low development, implementation and maintenance costs, small size, low weight, low probability of interception and avoidance of electromagnetic compatibility or environmental impact problems. All of these features are a result of the use of non-cooperative broadcast communications, radar or radionavigation transmitters, as Illuminators of Opportunity (IoOs), rather than a dedicated radar transmitter [1]. A PRS is a multi-static system that allows multiple configurations depending on the number of considered IoOs and receivers, with the objective of detecting targets and estimating their parameters (such as position and velocity). The radar performance is strongly determined by the exploited IoO waveform and the geometry of the radar scenario. The use of IoOs gives rise to complex processing architectures, but thanks to the availability of Field-Programmable Gate Array (FPGA)-based programmable hardware platforms and Graphic Processing Units (GPU), real-time processing is feasible. Due to the lack of control over the transmitter, two channels are usually used (Figure 1): a reference channel (to acquire the signal transmitted by the IoO) and a surveillance one (to capture the target echoes). To estimate target dynamics information, delay and Doppler-shifted copies of the reference signal are correlated with the surveillance channel in order to generate the Cross-Ambiguity Function (CAF). The received target echoes are extremely faint; therefore, high gain antennas are required in the acquisition stage. If only a single antenna is used in the surveillance channel, the associated narrow beamwidth (due to the inverse relation between antenna gain and beamwidth) leads to a considerable reduction of the coverage area and makes angular discrimination at the detector level unfeasible. Array processing and digital beamforming techniques have been proposed as a solution for PRS in several works. An FM circular array was considered in [2; 3] to obtain one reference and several surveillance beams. In [4; 5], a circular antenna array with elements for the VHF-range (150-350 MHz) and the UHF-range (400-700 MHz) is used to exploit alternatively Digital Audio Broadcasting (DAB) or Digital Video Broadcasting-Terrestrial (DVB-T) signals. Two-stage beamforming methods for low complexity Constant False Alarm Rate (CFAR) detection and estimation of the angle of arrival in DVB-T-based PRS have been proposed and tested in [6; 7]. In this paper, instead of a Uniform Linear Array (ULA), a spatially-Non-Uniform Linear Array (NULA) for the surveillance channel of a DVB-T passive radar demonstrator, IDEPAR (Improved Detection Techniques for Passive Radars) PRS, is considered. IDEPAR was designed and developed for terrestrial and maritime scenarios, and its capabilities were evaluated in [8; 9; 10; 11; 12; 13; 14]. Taking into consideration the IDEPAR design requirement of using Commercial Off-The-Shelf (COTS) components to the greatest possible extent, the array is based on commercial UHF antennas. The advantage of the NULA is based on improving the radiation beam pattern of a linear aperture of length L with uniformly-spaced array elements [15; 16]. In the considered architecture, there are different receiving chains, one per single radiating element, to generate the snapshots (vector composed of complex samples associated with the output of each sensor). Snapshot models can be developed in the frequency or time domain [15]. In this paper, the spatial filtering is applied in the frequency domain to take advantage of the processing gain of the PRS.