Different from conventional phased-array providing only angle-dependent beampattern, frequency diverse array (FDA) produces angle-range-dependent and time-variant transmit beampattern. Existing investigations show that FDA offers improved performance in interference suppression and target localization, but the time-variant beampattern will bring interferences to subsequent matched filtering. More seriously, the range-dependent signal phase may be canceled out in the filtering process. In fact, traditional single-channel receiver does not fully exploit the multicarrier feature in FDA signals. In this paper, we propose a multichannel matched filtering structure with considering the time-variance property for receiving pulsed-FDA signals. A coherent pulsed-FDA radar signal model to deal with the angle-range-dependent and time-variance problem is devised under additive colored Gaussian noise scenarios, followed by the corresponding waveform design principle. Moreover, closed-form expressions of the output signal-to-interference-plus-noise ratio and Cramér-Rao bounds for angle and range are derived. The proposed receiver design approach and corresponding theoretical performance derivations are verified by extensive numerical results.

Frequency diverse array (FDA) is an emerging technology, the hybrid of FDA and multiple-input-multiple-output (FDA-MIMO) under monostatic scenarios has received much attention in recent years. However, little work have been done for bistatic FDA-MIMO radar. In this paper, we investigate strategies on estimating direction-of-departure (DOD), direction-of-arrival and range for bistatic FDA-MIMO radar. Our strategies have two aspects. First, nonlinear frequency increments including both subarray and random modes are employed to overcome the problem that the DOD and range parameters of FDA transmitting steering vectors are coupled. Second, in order to reduce the computational complexity associated with the 3-D spectral peak searching algorithms, estimation of signal parameters via rotational invariance technique and parallel factor algorithms with their corresponding phase ambiguity resolving methods, are proposed for subarray and random modes, respectively. Both of the two algorithms perform well while the range parameter of targets satisfy a range constraint criterion. This criterion can also be used for designing frequency increments of bistatic FDA-MIMO radar. Additionally, the Cramér-Rao bound of bistatic FDA-MIMO radar and the algorithm performance analysis consist of identifiability and complexity are derived. All the proposed methods are verified by both theoretical analysis and numerical simulations. And satisfactory results are achieved.

Frequency diverse array (FDA) has received much attention, but little work about FDA receiver architectures and receiver processing algorithms have been reported. In this paper, we analyze the localization performance of FDA radar with a two-stage estimator. Three FDA receive architectures are discussed and compared with the phased-array (PA). In order to overcome disadvantages of the monochromatic FDA radar signal model adopted in the literature, which ignores the coherent transmit gain in FDA radar, we formulate a bandwidth model for a general FDA radar received signals including both non-overlapping and overlapping spectra. The localization performance are assessed by the Cramer-Rao bound (CRB) and receive signal noise ratio (RSNR). The proposed model provides more accurate representation of FDA radar received signals and more reasonable comparisons between FDA and PA radars. Additionally, a fast two-stage estimator is proposed to reduce the 2D-MUSIC computation complexity. All proposed methods are verified by both theoretical analysis and numerical results.

A single radio frequency (RF) channel digital beamforming (DBF) array antenna based on compressed sensing (CS) was proposed to reduce the hardware costs, power consumption, and the design complexity of large-scale DBF systems. For DBF antenna systems, the general way to obtain the signals received by each sensor is to connect each sensor to an independent RF receiver channel. When the array contains a large number of sensors, the multichannel signal sampling scheme makes the system power hungry and expensive. A time sequence phase weighting (TSPW) technology provides a solution to this problem. The TSPW antenna array can obtain the signals received by each sensor with only one RF receiver channel by sequentially sampling the specific single channel signals, which are produced by the TSPW array. However, the number of single channel samples scales linearly with the number of sensors. The sampling time will be so long as to be unacceptable when the array contains a large number of sensors. To overcome this problem, we introduced CS theory to the TSPW array. With the help of CS, the sampling frequency can be simultaneously reduced in both time and spatial domain, which correspond to the reduction of the number of both the samples and sensors. Theoretical analyses have been proposed to show the conditions that should be met for successful reconstruction. The simulation results from an X-band array with an aperture size of 80λ under the signal-to-noise ratio of 15 dB and the scenario of six targets showed that the proposed array could save above 63.1% of sensor numbers and above 84.4% in sampling time when compared with those of conventional TSPW arrays.

In modern communication and radar applications, large-scale sensor arrays have increasingly been used to improve the performance of a system. However, the hardware cost and circuit power consumption scale linearly with the number of sensors, which makes the whole system expensive and power-hungry. This paper presents a low-cost nested multiple-input multiple-output (MIMO) array, which is capable of providing $O\left(2N^2\right)$ degrees of freedom (DOF) with $O\left(N\right)$ physical sensors. The sensor locations of the proposed array have closed-form expressions. Thus, the aperture size and number of DOF can be predicted as a function of the total number of sensors. Additionally, with the help of time-sequence-phase-weighting (TSPW) technology, only one receiver channel is required for sampling the signals received by all of the sensors, which is conducive to reducing the hardware cost and power consumption. Numerical simulation results demonstrate the effectiveness and superiority of the proposed array.