Peter G. Vouras

Robust Transmit Nulling in Wideband Arrays

The ability to create nulls in the transmit pattern of a phased array antenna has many applications in communication and radar systems, including interference and clutter mitigation. This paper describes the implementation of transmit nulls in wideband arrays through the use of a filter bank inserted behind each array element. The filter bank decimates and partitions the transmit signal into independent subbands and utilizes a tapped delay line (TDL) in each subband to form frequency invariant spatial nulls in the arrays transmit pattern. New contributions developed in this paper include an algorithm for determining the TDL coefficients and a novel band partitioning scheme based on principal component filter banks (PCFBs), which is shown to be optimal for minimizing spectral errors if the TDL coefficients are quantized. Numerical techniques are presented for approximating ideal PCFBs using practical paraunitary filter banks (PUFBs) and perfect reconstruction filter banks (PRFBs).

Application of adaptive beamforming techniques to HF radar

This paper evaluates the performance of several adaptive beamforming techniques applied to the problem of cancelling interference in a high frequency (HF) radar with transmitter and receiver physically separated by large distances. The difficulties posed by mitigating interference in a HF radar are fundamentally different in many aspects from the adaptive cancellation problem in more conventional phased array radars operating at higher frequencies. Some of the issues specific to adaptive cancellation in HF radar will be addressed in this paper and performance results will be presented using measured data.

Sample support requirements for nonlinear adaptive beamforming

In theory, nonlinear adaptive beamforming techniques which form an extended virtual array from a sparsely populated physical array offer significantly enhanced adaptive degrees of freedom towards mitigating environmental interference as opposed to conventional linear beamformers. A neglected practical issue however, central to the implementation of nonlinear beamformers in radar, is an accurate determination of the data support necessary for computing the adaptive weights and the adapted array output. This paper investigates the data support requirements for a new nonlinear beamformer operating on the streaming output of a multichannel array. The array exists within a quasi-stationary or slowly varying environment where more interference sources are present than array elements.

Design of FIR Paraunitary Approximations to Principal Component Filter Banks

In this paper, we present two new algorithms for designing finite impulse response (FIR) paraunitary (PU) filter banks that are optimal approximations to ideal principal component filter banks (PCFBs). The first algorithm is optimal in the sense that it minimizes the mean square error between the desired response and the approximation. The second algorithm is optimal in the sense that it minimizes the maximum error. Both algorithms utilize a complete parameterization of FIR PU filter banks in terms of Givens rotation building blocks, and jointly optimize all the filters in the filter bank.

Wideband Adaptive Beamforming Using Linear Phase Filterbanks

This paper describes the use of linear phase filter banks to perform wideband adaptive beamforming. The application of two types of filter banks is investigated. First, a simple discrete Fourier transform filter bank (DFTFB) is examined, and second a linear phase paraunitary filter bank (LPPUFB) designed using nonlinear optimization techniques is reviewed. For both filter banks, it is shown that computing and applying the optimal beamformer weights independently for different frequency bands yields better performance than a narrowband beamformer.

Fully Adaptive Space-Time Processing on nested arrays

This paper describes fully adaptive nonlinear space-time processing on nested arrays. Nested arrays are sparse arrays that in conjunction with nonlinear processing of the received signals enable more adaptive degrees of freedom than a conventional linear beamformer would allow. The Space-Time Adaptive Processing (STAP) architecture proposed in this paper consists of a nested array that samples received pulses on a nested temporal interval. The sparse spatial and temporal sampling pattern of the proposed architecture together with the nonlinear processing performed on the received pulses makes this STAP architecture fundamentally different from conventional STAP arrays. Simulated results for an airborne platform illustrate angle-Doppler nulling performance for illuminated ground clutter and for jamming interference.

Multistage Adaptive Pulse Compression

Many modern radar systems employ pulse compression to maximize the energy on target while maintaining high range resolution. For a solitary point target in white noise, employing a matched filter on receive will maximize the target signal-to-noise ratio (SNR) at the output of the receiver. The matched filter itself is a time-reversed version of the transmitted waveform which is convolved with the received time series to pulse compress the data. A drawback to the matched filter receiver is the range sidelobes which extend on either side of the point target and may mask another weaker target. To reduce range sidelobes after pulse compression, novel adaptive pulse compression techniques have been developed. One such technique is the Reiterative Minimum Mean Square Error Adaptive Pulse Compression (RMMSE-APC) algorithm. This algorithm employs an optimal compression filter at each range bin and significantly reduces the range sidelobes in the vicinity of large targets. In this paper, a pulse compression filter with output identical to the RMMSE filter is derived by employing a multi-stage decomposition of the Wiener filter. A reduced rank version of the Multi-Stage Wiener Filter (MSWF) with lower computational complexity can be created by pruning the number of stages in the decomposition.

Principal component filter bank for band partitioned sidelobe cancellation

Principal component filter banks (PCFBs) have been shown to be optimal, if they exist, for a variety of signal processing applications. Ideally, the filters in PCFBs are the eigenvectors of the spectral density matrix of the input random process and therefore depend on the statistics of the input random process. This paper investigates the application of PCFBs to the problem of band partitioned sidelobe cancellation for a two channel canceler. In this context, the filters are the eigenvectors of the cross-spectral density matrix. The ideal filters have an infinite impulse response and are not realizable. Therefore, they must be approximated. Several algorithms are available, but in this paper, the PCFB filters were approximated using a simple, although suboptimal, window method. The cancellation performance of the PCFB was compared to the performance of a time domain GramSchmidt canceler, and band partitioned cancelers utilizing a dyadic filter bank, a wavelet packet filter bank (WPFB), a cosine modulated filter bank (CMFB), and a maximally decimated discrete Fourier transform filter bank (DFTFB). The performance of the approximated PCFB was found to be better than the time domain and dyadic cancelers, but not as good as the DFT, wavelet packet, and cosine modulated cancelers. This shortfall is attributed to the approximation of the ideal PCFB filters.

Multirate processing using nested sampling

This paper describes the multirate processing of random signals sampled on nested intervals. Nested sampling intervals consist of nonuniformly spaced samples formed by concatenating two or more smaller intervals each with uniform sampling. By filtering a vectorized version of the signal power spectral density matrix, the input-output behavior of conventional filter banks can be replicated. This type of processing is especially useful in multifunction radars that must perform multiple tasks simultaneously but lack the capability to form multiple beams on receive. By performing Doppler processing for a given mainbeam pointing direction using only a sparse subset of uniformly transmitted pulses, the radar is able to point the mainbeam in other directions and execute different tasks in a time-multiplexed fashion. Simulated examples are presented which describe the application of the proposed technique.

Robust transmit nulling in phased array antennas

The ability to create nulls in the transmit pattern of a phased array antenna has many applications for radar systems, including interference and clutter mitigation. Most nulling techniques introduce small perturbations in amplitude and phase, or phase-only, at each element of the phased array. For practical reasons, phase-only perturbations are desired and they create acceptable rms levels of null depth. However, the phase shift at each element will vary with the frequency of the transmitted signal. As a result, the depth and pointing accuracy of the transmit null will not be uniform over the bandwidth of the transmitted signal. This paper will describe some of the inherent limitations in achieving robust transmit nulling performance over a wide bandwidth when using phase-only, open-loop control on a typical phased array antenna. Some solutions to overcome these limitations and improve the performance of transmit nulls will be proposed.