<dfn id="gacgu"></dfn>
fastslam 又稱(chēng)為rao-blackwillisd slam方法，源碼提供fastslam1.0 和2.0的matlab源碼。
標(biāo)簽： rao-blackwillisd fastslam slam
上傳時(shí)間： 2013-12-26
上傳用戶(hù)：xmsmh
熟悉A/D轉(zhuǎn)換 軟件思路：選擇RAO做為模擬輸入通道； 連續(xù)轉(zhuǎn)換4次再求平均值做為轉(zhuǎn)換結(jié)果 最后結(jié)構(gòu)只取低8位 結(jié)果送數(shù)碼管的低3位顯示
標(biāo)簽： 轉(zhuǎn)換 RAO 8位 模擬輸入
上傳時(shí)間： 2014-01-21
上傳用戶(hù)：eclipse
軟件思路：選擇RAO做為模擬輸入通道 連續(xù)轉(zhuǎn)換4次再求平均值做為轉(zhuǎn)換結(jié)果最后結(jié)構(gòu)只取低8位結(jié)果送數(shù)碼管的低3位顯示 硬件要求：撥碼開(kāi)關(guān)S14第2位置ON，第1位置OFF撥碼開(kāi)關(guān)S6全部置ON，S5第4-6位置ON，第1-3位置OFF為不影響結(jié)果，其他撥碼開(kāi)關(guān)置OFF。
標(biāo)簽： RAO S14 轉(zhuǎn)換 軟件
上傳時(shí)間： 2017-08-04
上傳用戶(hù)：zhouli
基于RBMCDA (Rao-Blackwellized Monte Carlo Data Association)方法的多目標(biāo)追蹤程序
標(biāo)簽： Rao-Blackwellized Association RBMCDA Monte
上傳時(shí)間： 2017-08-29
上傳用戶(hù)：tb_6877751
This paper examines the asymptotic (large sample) performance of a family of non-data aided feedforward (NDA FF) nonlinear least-squares (NLS) type carrier frequency estimators for burst-mode phase shift keying (PSK) modulations transmitted through AWGN and flat Ricean-fading channels. The asymptotic performance of these estimators is established in closed-form expression and compared with the modified Cram`er-Rao bound (MCRB). A best linear unbiased estimator (BLUE), which exhibits the lowest asymptotic variance within the family of NDA FF NLS-type estimators, is also proposed.
標(biāo)簽： performance asymptotic examines non-data
上傳時(shí)間： 2015-12-30
上傳用戶(hù)：225588
In this article, we present an overview of methods for sequential simulation from posterior distributions. These methods are of particular interest in Bayesian filtering for discrete time dynamic models that are typically nonlinear and non-Gaussian. A general importance sampling framework is developed that unifies many of the methods which have been proposed over the last few decades in several different scientific disciplines. Novel extensions to the existing methods are also proposed.We showin particular how to incorporate local linearisation methods similar to those which have previously been employed in the deterministic filtering literature these lead to very effective importance distributions. Furthermore we describe a method which uses Rao-Blackwellisation in order to take advantage of the analytic structure present in some important classes of state-space models. In a final section we develop algorithms for prediction, smoothing and evaluation of the likelihood in dynamic models.
標(biāo)簽： sequential simulation posterior overview
上傳時(shí)間： 2015-12-31
上傳用戶(hù)：225588
We present a particle filter construction for a system that exhibits time-scale separation. The separation of time-scales allows two simplifications that we exploit: i) The use of the averaging principle for the dimensional reduction of the system needed to solve for each particle and ii) the factorization of the transition probability which allows the Rao-Blackwellization of the filtering step. Both simplifications can be implemented using the coarse projective integration framework. The resulting particle filter is faster and has smaller variance than the particle filter based on the original system. The convergence of the new particle filter to the analytical filter for the original system is proved and some numerical results are provided.
標(biāo)簽： construction separation time-scale particle
上傳時(shí)間： 2016-01-02
上傳用戶(hù)：fhzm5658
％ PURPOSE : Demonstrate the differences between the following ％ filters on a simple DBN. ％ ％ 3) Particle Filter (PF) ％ 4) PF with Rao Blackwellisation (RBPF)
標(biāo)簽： Demonstrate differences the following
上傳時(shí)間： 2016-01-07
上傳用戶(hù)：cjf0304
This paper studies the problem of tracking a ballistic object in the reentry phase by processing radar measurements. A suitable (highly nonlinear) model of target motion is developed and the theoretical Cramer—Rao lower bounds (CRLB) of estimation error are derived. The estimation performance (error mean and
標(biāo)簽： processing ballistic the tracking
上傳時(shí)間： 2014-10-31
上傳用戶(hù)：yyyyyyyyyy
This paper studies the problem of tracking a ballistic object in the reentry phase by processing radar measurements. A suitable (highly nonlinear) model of target motion is developed and the theoretical Cramer—Rao lower bounds (CRLB) of estimation error are derived. The estimation performance (error mean and
標(biāo)簽： processing ballistic the tracking
上傳時(shí)間： 2014-01-14
上傳用戶(hù)：奇奇奔奔
蟲(chóng)蟲(chóng)下載站版權(quán)所有 京ICP備2021023401號(hào)-1
<small id="i6wwi"></small>