International Journal of Antennas and Propagation

Volume 2016, Article ID 1892512, 6 pages

http://dx.doi.org/10.1155/2016/1892512

## Adaptive Radio Frequency Interference Mitigation for Passive Bistatic Radar Using OFDM Waveform

School of Information Engineering, Nanchang University, Jiangxi 330031, China

Received 10 March 2016; Revised 30 June 2016; Accepted 25 July 2016

Academic Editor: Lorenzo Crocco

Copyright © 2016 Zhixin Zhao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### Abstract

High frequency passive bistatic radar (HFPBR) is a novel and promising technique in development. DRM broadcast exploiting orthogonal frequency division multiplexing (OFDM) technique supplies a good choice for the illuminator of HFPBR. HFPBR works in crowded short wave band. It faces severe radio frequency interference (RFI) problem. In this paper, a theoretical analysis of the range-domain correlation of RFI in OFDM-based HF radar is presented. A RFI mitigation method in the range domain is introduced. After the direct-path wave rejection, the interference subspace is constructed using the echo signals at the reserved range bins. Then RFI in the effective range bins is mitigated by the subspace projection, using the correlation among different range bins. The introduced algorithm is easy to perform in practice and the RFI mitigation performance is evaluated using the experimental data of DRM-based HFPBR.

#### 1. Introduction

HF passive bistatic radars (HFPBR) are a subset of bistatic radars exploiting noncooperative HF transmitters of opportunity. They have gained more and more attention in detecting low-flying and ocean ship targets as well as some remote sensing applications, for their advantages of both PBR (including having lower cost, being harder to detect, and being capable of directly and naturally facing the spectral compatibility issue) and HF over-the-horizon radars [1]. Digital broadcast is taking the place of traditional analog broadcast. With the trend of this, much research and development have been invested in PBR exploiting digital broadcast transmitters as a surveillance sensor in recent years [1–5]. DRM broadcast exploiting orthogonal frequency division multiplexing (OFDM) is accepted as the only standard for HF band by ITU-R, which has got rapid development globally, especially in Europe, in past years [6–8]. The use of OFDM signal provides frequency diversity to the system [9, 10]. DRM broadcast transmitter supplies good choices for the illuminator of HFPBR system, owing to its good signal properties and excellent low-altitude coverage.

RFI is introduced in HF radar since the frequency band 3–30 MHz is shared by many radio services. It is also inevitable for HFPBR because DRM broadcasts have to share the usage of the current equipment and frequency bands of the analog transmission systems over a period of time called transition period. In HFPBR, surveillance and reference channels are needed to receive echoes of interest and reference signal, respectively. RFI will raise up the noise floor of the range-Doppler (RD) plot after the two-dimensional cross-correlation function (2D-CCF) when appearing in the surveillance channel. When the RFI to target echo ratio increases, target’s peak-to-noise-floor ratio will decrease or the target would be masked completely [11]. Thus, RFI will lead to performance deterioration.

However, RFI problem in HFPBR is mentioned a little in the open literature. Many temporal or time-frequency techniques are also discussed to remove RFI in HF active radar systems, but they are based on chirp signals or others [12–15]. In this paper, RFI in OFDM-based HFPBR is investigated. OFDM technique is a multicarrier modulation method with up to hundreds of subcarriers. For HFPBR systems with OFDM waveform, RFI will show different characteristics, because the radar waveform of PBR is new and different, which exploits OFDM technique and is originally designed for broadcasting. Thus the RFI model should be reanalyzed during PBR signal processing and then a suitable method can be proposed. In this paper, a theoretical analysis of the range-domain correlation of RFI in OFDM-based HF radar is presented. The results provide a theoretical basis for RFI mitigation in the range domain. So a new RFI mitigation method is introduced. RFI is assumed stationary along each range swath and for a subset of slow-time data. First, after the direct-path wave is rejected, the echo signals at the far range bins seemed to only have the interference and noise, without the sea echo or target. Then the interference subspace is constructed using the echo signals at far range bins. Finally, RFI in the effective range bins is mitigated by projecting them onto the orthogonal subspace of the interference subspace, using the correlation among different range bins. The introduced method is easy to perform in practice and has been evaluated using the experimental data of DRM-based HFPBR.

This paper is organized as follows. Based on the signal processing diagram and waveform of PBR systems, the range-domain correlation of RFI in OFDM-based PBR is introduced in Section 2. The new RFI mitigation method is presented in Section 3. The analysis results on real data are given in Section 4 and conclusions are drawn in Section 5.

#### 2. Range-Domain Correlation of RFI in OFDM-Based PBR

The RFI characteristics in radar signals are closely related to the waveform used by the radar system and the radar signal processing scheme. According to the signal processing scheme for HFPBR with OFDM waveform given in [11], the echo signals are filtered by the matching filter of the reference signal to acquire the echo signals at each range bin.

OFDM technique is exploited in DRM broadcast to cope with the complex environment in HF band. The transmitted baseband complex-envelope DRM signal during each symbol interval can be described by the following expression [16]: where denotes the carrier number from to ; is the frequency for carrier ; is the carrier frequency interval; and is the modulated complex cell value for carrier .

In the receiver, baseband RFI is considered as a narrow band signal that can be represented as , which is the stationary baseband interfering signal with zero mean and bandwidth of .

The range correlation is actually processing the received signal by a filter matched to the transmitted OFDM signal , sowhere the superscript denotes conjugate operation.

Thus the output of the range correlation of the RFI can be expressed as where denotes the convolution operator and . It shows that the discrete samples of () actually are the Inverse Discrete Fourier Transform of . Assuming and are the corresponding discrete time-domain expressions of and , the discrete samples of can also be seen as . It also shows that the interference after range correlation extends to all range bins.

The correlation function of the interference in the range domain can be written aswhere is the expectation operator. Obviously, the corresponding power spectrum is . It shows that the correlation time of the incident inference is related to inference bandwidth and the distribution of the modulated complex cell value . Obviously, owing to the different waveform, the relevant result of RFI in OFDM-based passive radar is different from the one in chirp signal-based radar [15].

#### 3. RFI Mitigation

The above analysis provides a theoretical basis for RFI mitigation in the range bin. As in DRM-based HFPBR, the mean of is 1 and the variance is also very small. Then the correlation time of the incident inference can be approximated as . Thus as long as the interference bandwidth is relatively small, the interference will be correlated over a large number of range bins which is more than the effective detection range bins, and it ensures the efficiency of the range-domain mitigation. An orthogonal projection filtering method for RFI mitigation in HFPBR is introduced in the following. The processing diagram is given in Figure 1.