Research Of Optimal Array Design And Parameter Estimation On Frequency Diverse Array

Different from phased-array and multiple-input multiple-output (MIMO) array, frequency diverse array (FDA) uses a small frequency increment across its array elements to produce range and angle dependent transmit beampattern. Due to its promising application potentials, FDA has received much attention in recent years. For the range and angle dependent beampattern, the FDA radar has potential great advantages in interferences suppressing, target resolution localization and RF stealth. Furthermore, FDA MIMO radar can estimate directly both the range and angle of a target, which is its unique capability not accessible for a conventional phased-array.Based on the above mentioned advantages, this paper analyzed the capability of FDA radar and investigates its performance in beamforming, parameter estimation and signal detection. This paper also exploited several promising applications of FDA radar, along with their advantages. The contributions of this paper are summarized as follows:(1) Two schemes are proposed to decouple the range and angle of FDA beampattern. Firstly, the FDA beampattern properties are investigated and compared with that of a phased-array radar. Based on the range and angle dependent beampattern, two FDA schemes are proposed to decouple the range and angle of a linear FDA beampattern, which produces point-shape range-angle beampattern. The first method is that each FDA element transmits multi-carrier frequency signals with linearly increasing frequency offsets. In doing so, a flexible beampattern design is allowed. But this method is difficult to realize for hardware systems. The second method is that each element transmits only a single-frequency signal, but nonlinearly increasing frequency increments are adopted. The performances of the designed beampatterns and their applications in estimating target parameters are investigated.(2) This dissertation extensively analyzes the impacts of frequency increment errors on the FDA beampattern. Since frequency increment errors are unavoidably existed in FDA radar systems, which will degrade the system performance, the possible FDA beampattern range and angle errors are derived by assuming uniformly distributed frequency increment errors. For stochastic frequency increment errors, the corresponding upper and lower bounds for FDA beampattern errors are derived. They are verified by numerical results. Furthermore, the statistical characteristics of the FDA beampattern with random frequency increment errors, which obey Gaussian distribution and uniform distribution, are also investigated. The simulation results verify the theoretical derivations.(3) This dissertation proposes a hybrid structure of FDA and MIMO radar for estimating the angles and ranges of targets. Furthermore, a range-dependent interference suppression approach via FDA MIMO radar is proposed. Simulation results show that the proposed FDA MIMO radar outperforms conventional MIMO radars in suppressing range dependent interferences and output signal-to-interference-plus-noise ratio (SINR) performance. Furthermore, by exploiting the range dependent transmit beampattern, the FDA MIMO radar can be used to estimate the angles and ranges of targets, which is not accessible for a conventional MIMO radar. Simulation results show that the dot-shape beampattern produced by the FDA MIMO radar means that it can estimate both the angle and the range of a target. The corresponding cramer-rao lower bounds (CRLB), root mean square errors and target resolution probability are extensively evaluated and simulated. Furthermore, a low-complexity algorithm is proposed to improve the computational efficiency in estimating the angle and range of a target.(4) An optimal design of FDA transmit array is proposed. To improve the performance of FDA MIMO radar in target localization, a subarray MIMO frequency diverse array (FDS MIMO) design scheme is proposed with CRLB optimization for range-dependent target localization. The design divides the transmit array into multiple subarrays, and joints the high gain of FDA and dexterity of MIMO radar. The objective function, namely, RMSE minimization is transformed into the CRLB minimization. The formulated CRLB minimization problem is easily resolved by general convex optimization tools, such as SeDuMi and SDPT3. The methods can improve the estimation performance of FDA MIMO radar greatly.(5) At last, the dissertation proposes a cognitive FDA MIMO radar with low probability of intercept (LPI) design. Inspired by cognitive radar scheme, two steps are proposed to achieve the LPI:The first step is to estimate the target parameters by FDA MIMO radar; the second step is to design the transmit array to minimize the energy in which the target is located and maximize the energy of the receiver. In the second step, the convex optimization and dichotomy are jointly used to obtain the optimal weighting matrix. The rank constrains method is used to derive the weighting vector. Simulation results show that the rank constrains method is better than the rand minimization in detection performance. Moreover, it decreases the interception risk and improve the receive probability. Therefore, compared with conventional radar, the designed FDA-MIMO radar has better LPI performance.