我心目中的英雄(1)

魔有魔道,神有神位。工程师心中有他自己的偶像和英雄。

(1)paul zarchan,MIT draper实验室高级工程师,战略战术导弹专家。

也许每一个中国搞导航制导与控制的博士生都读过他写的书,至少理工大这边几乎是人
手一册。

Tactical and Strategic Missile Guidance,这本书背面有他的玉照。

Fundamentals Of Kalman Filtering: A Practical Approach

第一次看到他的书是在国图的新书阅览室,他的书被印爆了。。硬皮精装书居然磨损的散架
了,可见其受欢迎程度之高。国图见这书如此受欢迎,愣是把它放在新书室里5年(一般新书只放3年)

以挣取巨额的复印费(5毛一页)。后来这书出了第二版,才把这书从新书架上撤下。

写控制和卡尔曼滤波的书汗牛充栋,不计其数,洒家读博期间多有涉猎,可是留下印象
最深的只有他这两本。

如果把写卡尔曼滤波的作者们象华山剑派那样分为两派气宗和剑宗,那么他老人家绝对
是剑宗中的风清扬了。工程师出身的他,写的书没有任何公式推导,代码占全书的1/3以
上,这种书确实是中国工程师的最爱。我不要推导证明,我要程序。如果没有他的书,
我们这些博士生要在黑暗中摸索很长一段时间。

所以他是我最为推崇的专家,我代表中国的博士生感谢他把他几十年的经验都写了出来



--
渐修顿悟通禅机,厚积薄发正可期。
知君非是蓬蒿辈,乘风步云上天梯。

转载于:https://www.cnblogs.com/Eufisky/p/8684839.html

This is a practical guide to building Kalman filters that shows how the filtering equations can be applied to real-life problems. Numerous examples are presented in detail, showing the many ways in which Kalman filters can be designed. Computer code written in FORTRAN, MATLAB®, and True BASIC accompanies all of the examples so that the interested reader can verify concepts and explore issues beyond the scope of the text. In certain instances, the authors intentionally introduce mistakes to the initial filter designs to show the reader what happens when the filter is not working properly. The text carefully sets up a problem before the Kalman filter is actually formulated, to give the reader an intuitive feel for the problem being addressed. Because real problems are seldom presented as differential equations, and usually do not have unique solutions, the authors illustrate several different filtering approaches. Readers will gain experience in software and performance tradeoffs for determining the best filtering approach. The material that has been added to this edition is in response to questions and feedback from readers. The third edition has three new chapters on unusual topics related to Kalman filtering and other filtering techniques based on the method of least squares.Chapter 17 presents a type of filter known as the fixed or finite memory filter, which only remembers a finite number of measurements from the past. Chapter 18 shows how the chain rule from calculus can be used for filter initialization or to avoid filtering altogether. A realistic three-dimensional GPS example is used to illustrate the chain-rule method for filter initialization. Finally, Chapter 19 shows how a bank of linear sine-wave Kalman filters, each one tuned to a different sine-wave frequency, can be used to estimate the actual frequency of noisy sinusoidal measurements and obtain estimates of the states of the sine wave when the measurement noise is low.
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