Study On MIMO Radar Adaptive Processing And Waveform Design

Multiple-input multiple-output (MIMO) radar is a new concept of radar systemproposed recent years. MIMO radar is implemented by multiple transmit antennas andmultiple receive antennas, and individual transmit antennas can transmit differentsignals. In general, MIMO radar can be categorized into two types according to thecorrelation coefficient of target echoes between antennas: MIMO radar with widelyseparated antennas and MIMO radar with collocated antennas. The first type of MIMOradar can observe a target from different aspects to overcome the target scintillation,thus it can improve detection performance. MIMO radar with collocated antennas is ageneration of traditional phased array radar with more spatial freedom and higherresolution. This type of MIMO radar can improve the performance of clutter andjammer suppression and the accuracy of target parameters estimation. Due to thosesuperiorities, collocated MIMO radar combined with space-time adaptive processing todetect moving target becomes a hot topic in MIMO radar research. In addition, sinceMIMO radar has more degrees of freedom, waveform design is a significant topic. Thisdissertation concerns problems related to STAP technologies in MIMO radar, includingrank analysis of clutter plus jamming covariance matrix, reduced-dimension STAPalgorithm and also develops problems related to MIMO radar waveform designincluding transmit beampattern synthesis and waveform design with priori information.The mainly content of this dissertation is summarized as follows:1. The covariance matrix structure of clutter plus jamming is analyzed forside-look airborne MIMO radar, and the upper bound on its rank is derived, whichequals the summation of clutter and jamming rank subtracting the jammer number.According to this, a certain range of jammer number is attained. If the number ofjammers is within this range，the clutter plus jamming covariance matrix is full rank forphased array radar, but rank deficiency for MIMO radar. As a result, the performance ofphased array radar deteriorates severely under this condition, meanwhile, theperformance of MIMO radar is much better, taking advantage of sufficient degrees offreedom to suppress clutter and jamming for MIMO radar. Simulational experimentsvalidate the above conclusion.2. A new reduced-dimension space-time adaptive processing algorithm is proposedto suppress clutter and jamming for airborne MIMO radar. The jamming plus noisecovariance is utilized to construct reduced dimension transform matrix joint with target space-time steering vector and clutter subspace matrix which can be implementedoff-line. The data dimension after reduced dimension transformation equals clutter rankplus one. Thus, the computational load and sample requirement for computing adaptiveweight are reduced apparently. Compared with other algorithms, this algorithmconverges faster, and the theoretical performance can approach that of full dimensionaladaptive processing. Numerical results show that the algorithm can achieve lesssignal-to-interference plus noise ratio loss than existed algorithm, especially with lessadaptive weight training samples.3. Airborne MIMO radar uses its temporal freedom and receiving&transmittingspatial freedom to suppress clutter, while it nulls jammers by only receiving spatialfreedom. Based on these characteristic, a novel two-stage method is presented in thispaper, which separates suppression of clutter and jammers into two sequential stages.First, jammers are nulled with partial receiving freedom, and dimension reduction isalso implemented. Second, matched-filtering is applied to the output data after jammersuppression, followed by clutter suppression using temporal and spatial freedom.Through the two-stage processing, transmitting spatial freedom can be fully utilized inclutter suppression together with reducing the computational load and samplerequirement effectively. Both theoretic analysis and simulation experiments presentthat，in the presence of strong jammers, performance of the proposal can approach tothat of the full dimension space-time adaptive processing for MIMO radar.4. To deal with low sidelobe transmit pattern design problem for MIMO radar, anew minimum peak-sidelobe or integrated-sidelobe transmit pattern optimizationalgorithm is proposed in this paper. Due to the optimization problem of minimizingpeak-sidelobe or integrated-sidelobe is non-convex, it is solved in two steps by theproposed algorithm. A convex problem is solved in the first step, and in the second step,the global optimum of original problem is attained by scale transformation of thesolution in the first step. The simulations show that the transmit pattern have lowerpeak-sidelobe or integrated-sidelobe with this algorithm than existed algorithm.Since the transmit waveforms are not orthogonal when the transmit beampattern isnot omnidirectional, the covariance matrix structure of clutter plus jamming is analyzedfor side-look airborne MIMO radar with arbitrary transmit waveform for this case. Theupper bound on the rank of covariance matrix of clutter plus jamming is derived, whichis up to the summation of clutter and jamming rank subtracting the number of jammers.The conclusion in the condition of transmitting orthogonal waveforms is a special caseof this conclusion. 5. In order to decrease output peak CSR (Clutter to signal satio) of ground basedMIMO radar system in detection of ground target, a MIMO radar waveform andreceived filter joint optimization algorithm is proposed based on definite clutter impulseresponse. Assuming the clutter impulse response is known and definite, the optimizationproblem is solved through alternative iteration, and the peak sidelobe of the targetoutput signal can be decreased at the same time. In the simulation, the clutter impulseresponse is estimated from real data. Our algorithm can get lower peak CSR than LFM(Linear frequency fodulated) signal. Thus, this algorithm can be used to detect slowvelocity or stationary ground target. However the output CSR with our algorithm issensitive to the perturbation of clutter impulse response, big variation occurs among theoutput CSR of multiple pulse, thus affect the detection of moving ground target.Subsequently, a robust waveform and received filter joint optimization algorithm isproposed to decrease the sensitivity to the perturbation of clutter impulse response. Themaximum of the perturbation component of output CSR is induced into the objectivefunction in this algorithm to decrease the effect of clutter impulse response perturbation.Through applying the optimized waveform and received filter to multi-pulse clutterimpulse response estimated from real data, although the output peak CSR is higher thanthat of previous algorithm, the variation of CSR among multiple pulse decreasesapparently, and the peak output CSR is lower than that of LFM signal.